Monday Apr 27, 2020
Monday Apr 27, 2020
Monday Apr 27, 2020
Welcome to the Beyond Your Research Degree podcast from the University of Exeter Doctoral College! The podcast about non-academic careers and all the opportunities available to you... beyond your research degree! In this episode PhD student Debbie Kinsey talks to Dr Caitlin McDonald, a University of Exeter alumni who now works at the Leading Edge Forum. Today Caitlin is recognised for her domain knowledge in qualitative methods like ethnography and participant-observation.
Music from https://filmmusic.io ’Cheery Monday’ by Kevin MacLeod (https://incompetech.com) License: CC BY (https://creativecommons.org/licenses
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Hello and welcome to the Beyond Your Research Degree podcast by the University of Exeter, Doctoral College
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My name's Dr Caitlin McDonald.
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I graduated in 2011 with a degree in Arab and Islamic studies from here at the University of Exeter at the Institute of Arab and Islamic Studies.
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And hard as it is to believe that it's now nine years later.
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It's it's really interesting to look back on what's happened since that time and
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consider the skills that I took away from the university and how I'm applying them now.
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So maybe to give you a bit of an update on where I am. I currently work as a digital anthropologist at an organisation called The Leading Edge Forum,
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which does technology and strategy research for large businesses and just in the
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Last month I was at the UN delivering a talk at the International Labour Organisation.
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I then hosted a dinner at the House of Lords about ethics. And I've done a range of interesting and exciting things since then.
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But it's really interesting to think about this particular month in particular
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and how that the kind of culmination of where I started and how I got here.
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So I started working at the Leading Edge forum about two years ago, and before that I was based at what was the Times educational supplement.
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But it's no longer known as that it's just the tes
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It's no longer owned by the Times, where I was working as a digital analyst, data analyst and working with data systems quite a bit.
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So all of that sounds really different than where I started, which was very much middle easy studies based, but really the kind of the through line.
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The thread for me was that a lot of the research that I was doing when I was doing my PhD was very digital ethnography based.
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So I was looking at patterns of knowledge and how they shift around the world, in particular for dancers who often for Middle Eastern dance,
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want to base their practise or to base the centre at the hub of their knowledge in Cairo or sometimes in Turkey or in other kinds of regions.
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But in my particular case, I was looking at dancers who had a dance tradition that is based out of Cairo.
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And what ended up happening was I did a lot of ethnography around in particular how people were using Facebook groups,
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but also other social media channels to spread the knowledge and in the creation of knowledge
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about how the dance kind of mythology and epistemology of what the dance meant to people.
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And while this doesn't sound really revolutionary now, way back in 2006, 2007, 2008, when I was first doing that, that was fairly new.
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You know, there weren't a huge amount of digital humanities tools at the time.
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And certainly we weren't using anything like this wonderful lab that we have now. I think this was the old print print shop at the time.
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So it was really interesting. But then what ended up happening is I went to do a very quantitative role,
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which when you become an anthropologist, you don't necessarily think of yourself as a quantitative person.
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Some might. I did not. But it was having that kind of digital skills component that really was able to help me make
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the transition from a very academic role into a much more kind of commercially minded role.
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And I didn't really intend to leave academia, but around the time that I was leaving, there were huge budget cuts.
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So there simply weren't the kind of resources available for people to have postdocs and subsequent academic careers in particular.
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As an immigrant to this country, I was I needed to have a role if I wanted to stay working here.
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That was not short term. So it had to be a Full-Time full contract.
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And luckily, I was able to find something that worked out, which was with the Tes
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and they really wanted someone who could help them to an extent of their research skills.
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But a lot of the role was really about the kind of Day-To-Day operational knowledge to help the business run.
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So that was very, very different from what I previously been doing.
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But having this kind of interrogative skills, those kind of basics of a humanities research skills,
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those basic social sciences research skills was really helpful or for doing things
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like helping question why a particular thing was being done in a particular way.
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In particular, I was doing a lot of kind of daily reporting of what was happening on the website and what kinds of numbers
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were coming back in terms of circulation and all those kinds of things that digital businesses do.
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And really, the thing that was extremely useful was being able to turn around and say, hey, is anyone actually reading this report?
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You know, something as simple as this ritual that we go through on a daily basis of producing these numbers.
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How are they feeding into our decision making?
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And in some senses, that questioning was perhaps not always very welcome, but it also was that helpful to create the conditions for change.
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And I think that the social sciences are not always really great about talking about
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the transferable skills outside of academia that absolutely do exist.
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And I think now we're starting to see in particular with another research area that I do, which is all around ethics.
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You're starting to see some of those kinds of questions emerging around.
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Who is in charge of this knowledge or what are the kinds of different weights that we put on how we assess particular aspects of
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artificial intelligence and its relevance and its usefulness and how is it relevant to and who's benefiting and who's not benefiting?
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And I think that having a general social sciences research background, regardless of whether your specialism is in ethics or in,
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you know, particular aspects of digital technologies, you know, having that kind of questioning mind is is a really useful thing.
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And I think that people who work in digital context are starting to appreciate those qualitative skills,
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again, in a way that perhaps has been a little bit subsumed recently. So those kinds of questions around how is this going to benefit not only direct
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users of our services or our products or whatever it is that we're building,
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but also that kind of contextual knowledge about how is this affecting other people who are going to be impacted by the decisions that we're making?
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There is renewed curiosity and interest in those kinds of decisions. And so increasingly, organisations,
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businesses and non-commercial organisations are looking to the humanities as well as
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engineering to to make up the body of knowledge of creating those products effectively.
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So I would say now is a really good time, actually, to be in the digital humanities.
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And to some extent, no matter what you're doing, your work is always going to have a digital component.
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So recognising that, you know, when you think about the degree that I did,
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which was very much based in transmission of knowledge and very much about dance,
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you wouldn't necessarily think that that would lead to where it did lead. But in other ways, it makes total sense.
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It was a logical chain of transmission. I was looking at the social components of how that knowledge was happening.
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And now we are even more immersed in digital technologies. Our careers are even more immersed in this, no matter who you are.
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So having that background of having done that, kind of that kind of study was really useful to get me where I am now.
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Yeah, it sounds really interesting. So it sounds like so
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all PhDs are very specific so yours was around dance and transmission of knowledge between dances and creation of knowledge in that way.
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But then it sounds you talk about thinking about things, those things more broadly in terms of the general skills we develop.
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And how did you find translating those things from kind of academic speak to then going into a non-academic, non-academic role?
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Yeah. I would say that initially it was a real challenge for me, partly because when I first was looking for a job,
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I still was applying for a very academic roles, as well as starting to look beyond that.
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So I was looking at a lot of roles in market research. I was looking at the National Centre for Social Research.
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I was looking at ESRA U.K. you know, you go places like that and they have a more kind of traditional, I would say, research bent.
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Whereas if you if you move into, you know, user research and a company, for example,
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and most organisations do have a user research arm if they have a digital component, even if that's not their kind of core business,
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but that the language of that is very different from what perhaps you might be talking about
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if you're coming out of the social sciences or have a real kind of pure research background.
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So but the advantage of being an anthropologist or a sociologist or someone who
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studies the way that people think about knowledge is that you can then apply
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all the research skills that you have to your own situation so you can notice
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the kinds of patterns of knowledge that are happening in your organisation.
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You can notice the particular language that people are using around things and say, OK, you know, this group is talking about doing AB testing.
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You know, I might describe that differently in my own historical research background or whatever it was.
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But actually, the actual things that you need to do, the mechanics of the research are the same.
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So simply learning the kind of patterns of the patterns of life and work in
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the organisation that you find yourself in is a really useful skill to apply.
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So I spent probably two or three years mostly working in a digital engineering team.
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People that were doing actual software creation. And my role there was to assist with data migration that was happening.
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So we essentially had a place that we'd been storing all of this hard quantitative data
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that we were collecting over the years about how that Web site that we had was being used.
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And then we were changing everything about the underlying infrastructure and technology that we had into a completely different data storage system.
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And my role is to make sure that as we were doing that, nothing got lost.
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The data was collected in the same way. Nothing was missing.
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Nothing suddenly looked out of place. And so part of that was doing things like mapping the infrastructure from how the old data system work,
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doing what's called an entity relationship diagram, and looking at what the new entity relationships would be.
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So the places where the data was collected from the stored.
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And as I was doing those, I was like, this is a lot like doing essentially is family tree diagrams.
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You know, it's very much the same thing where you're looking at where are things transmitting from A to Z.
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So you can use all those kinds of same skills. And also just the kind of.
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That sense that I would get when I would go in and if I didn't know what people were
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talking about or if I felt like there was something unspoken or something happening,
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I didn't quite understand, I would behave exactly as though I were doing ethnography with a community,
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which is to try and treat the knowledge that I was a part of as being something that was that I was studying, you know.
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And so kind of having that observational hat on.
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First of all, it really helped defuse some situations that could have otherwise been quite personally demanding.
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Because if you just view it as I'm learning about what's going on within this group,
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then you're kind of personal sense of responsibility about that while still high because you were working there.
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It doesn't feel quite so rooted in your own sense of identity, I suppose,
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because you can also treat it as I'm viewing this as objectively separate from myself.
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And also then, you know,
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eventually you will pick up the lingo and you will learn the skills and you will realise the patterns that are happening within your organisation.
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And that's really helpful for putting the right pieces in place at the right time to achieve the things that you want to achieve in your career.
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Yeah, yeah. It's kind of like learning the language when you're there using those skills.
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You already have to kind of pick up on that. Precisely.
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Yeah. And how did you find it kind of before that stage, kind of making applications,
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trying to write and tailor things in such a way that you're using a language you're not quite sure of yet?
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And kind of that probably is the hardest piece.
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I would say, because you're not yet immersed enough in the transition that you want to make.
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To really know what you need to say so that your legitimacy of knowledge in that spaces is understood.
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And you also simply don't have the connections, perhaps, that you would do once you've moved into the space.
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So I'd say if I were going to do anything differently, probably what I would do is, you know,
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and especially for students who are listening to this now that are maybe in their first or second year,
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I would have spent a little bit more time thinking about how am I going to make the
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kinds of connections I want to make to understand the spaces that are available to me,
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like what are the options that are out there? And, B,
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make the Connections to really form the right network so that at the right time I have the right information about what roles are available and
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potentially who can introduce me to the right kind of person to to know about a job that's that's out there and the right kinds of skills.
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So because skills do change in terms of need, employer need, and what they're looking for will change over time.
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So having an idea of how that space is shifting will allow you to see not only what's on the on the market right now or what's needed in the market,
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but you can get an understanding of what's going to be needed by the time I leave,
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because you can kind of observe the trends that are happening and say, OK.
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So if I put some resources into, for example, learning how to do network mapping or doing a bit more on the kind of digital skill side,
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then I'll be more valuable than if I'm spending time doing something else. Which isn't to say, of course, that you shouldn't focus on your degree.
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I mean, you know, it's such a kind of you have to get over that hurdle more than anything else.
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Right? That is the thing to get through. But I'd say a really crucial skill is networking.
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And I know that everyone always says that. And people find it can find it very overwhelming.
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But I think the thing to remember is networking is a skill that allows you to understand
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some knowledge that's out there in the world that you don't yet have in an informal way.
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So if you view it in that sense, then it can be less overwhelming.
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And I found as well, once I started learning to have an objective when I went to a networking event.
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So I go to a lot of digital skills, meet ups in London, or I try and attend a lot of webinars or whatever it is I'm trying to learn about.
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I look for places where I can find that information and in particular I potentially can
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share some information as well because people are always willing to engage with you.
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First of all, if you're interested in them and ask them questions, everyone loves talking about themselves.
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This is like the crucial skill of good networking is if you can get someone, if you can express interest in them.
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People are usually very willing to tell you more about what they're doing,
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but also people are usually have some kind of a need that if you can fulfil that need in some way,
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like having a slightly adjacent skill or a different skill that they're looking for, then they'll want to talk to you as well.
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So so building that skill of saying, OK, there is a big data meetup on Wednesday, I'm going to go and
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My goal is to find out either a little bit more about this particular topic or to meet someone that works in this
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business or to find someone that has this job title and just speak to them a little bit about whatever my objective is.
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Having that focus can really, really make it much easier because you feel less overwhelmed by the idea of networking in general.
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That can. Huge kind of topic and kind of focussing it on something smaller to achieve can make can make life just a little bit less overwhelming.
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Yeah, yeah, definitely. I think a lot people do get it. Oh, you've got to network.
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But then what does that really mean? What does it look like in practise. They kind of.
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Yeah. So to get tip of going to something with an objective and kind of having a little bit of reciprocity in that,
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like maybe there's two things you can offer as well as getting people to talk about themselves.
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Yeah. And honestly, the other thing that I would say, which is a really good tip, is even if you're fairly early in your career,
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especially if you're looking at a non-academic role, getting up there and being a speaker.
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So, you know, it gives it gives you a chance to showcase what you're doing or the kinds of knowledge and skills that you have.
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But it also gives people an excuse to talk to you at a networking event.
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And even if you're an introvert, actually, as scary as it could be to go on stage,
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giving a talk is a really excellent way of putting the burden on others to come and talk to you so you don't have
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to feel like you're trying to muscle your way into someone else or to identify a friendly face in the crowd,
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because everyone knows that you're so and so talked about the thing and then they might want to come ask you questions.
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So it's a really great way of, you know, it's essentially you saying I'm here, I can talk about this.
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And I'd say the real value is that in the personal connections, the one on one connections that you make after you've given the talk.
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So even a short you know, in particular, when I think about the technology team,
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which is mostly what I work in, there are tons of events, in particular London, where I live.
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You could probably go to multiple. You'd have your choice of events to go to every evening.
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And typically they're very short form talks, two to three minutes about a subject of interest.
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So there's usually lots of opportunities to get in and kind of on the ground floor of the ladder of speaking, as it were.
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If you're in a place that has less accessible resources in that way, there are definitely a lot of online resources.
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And in particular, I think now that there is so much fear about physically being lots of people together,
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lots of the kinds of events that I would typically have gone to are going to be thinking about moving online more and more.
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And the way that we develop essentially digital etiquette.
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So, you know, how people develop those kinds of informal connections is going to become increasingly important.
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You know, it's relatively easy to put together a podcast or a webinar that is one way broadcast content,
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but creating those connections that those networking events are really valuable for.
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There are very few ways that people are good at that right now. But I think increasingly that's a thing that people will get good at.
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So I'd say look for opportunities in that space where you can not only watch a piece of content,
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but also in some way contribute to an ongoing dialogue and meet people through that kind of a mechanism.
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I'm trying to think of other examples of good kind of asynchronous or at a distance ways that people can learn and connect with one another.
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I subscribe to a lot of newsletters about such just some interest to me professionally as well.
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Usually reaching out to someone and saying, I read this thing or I have a question about whatever it is,
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you won't always have a hundred percent success so that people will get a lot of demands on their time,
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particularly as they get more skilled or experienced in their space.
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But often people are again willing to talk about something or willing to connect with you,
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you know, to answer a question or to be involved or engaged in something.
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People are typically very generous with their time, you know, especially if you're only asking for 10 minutes or, you know,
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whatever it is, a small or small chunk of time is usually a good way to go in, particularly if you can be specific about your ask.
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That really helps people to engage with you quickly is instead of being like, hey, I read your thing, will you be my mentor?
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That's that's often too open ended. But if you say I read your thing, it was interesting.
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Specifically, I have a question about blah. You can often then open a dialogue in that way.
00:18:57,000 --> 00:19:05,000
Yeah. So it kind of being specific and kind of very much time limited when you're asking of people.
00:19:05,000 --> 00:19:11,000
And yeah. And it's really interesting to think about kind of non sort of Face-To-Face in person ways you can do networking.
00:19:11,000 --> 00:19:15,000
I think a lot of people think of networking as you got to go to this event and a lot
00:19:15,000 --> 00:19:18,000
of PGRs are part time or they have caring responsibilities and they just think,
00:19:18,000 --> 00:19:23,000
oh, I just can't do that. Actually, there are all these other ways that you can get involved.
00:19:23,000 --> 00:19:28,000
Yeah. And like I say, I think that those kind of online and asynchronous abilities are where the necessity for those
00:19:28,000 --> 00:19:34,000
is going to become increasing over the next few months and probably years after that as well.
00:19:34,000 --> 00:19:39,000
You know, because businesses have long been looking for ways to encourage less business travel, for example.
00:19:39,000 --> 00:19:43,000
And it's always, oh, it's too hard. There's no way to do this. It's impossible.
00:19:43,000 --> 00:19:49,000
And one of my current research areas is how digital technologies are actually changing the physical spaces that people work.
00:19:49,000 --> 00:19:57,000
And so right now is a real kind of fascinating live experiment for me to watch the way the businesses are responding to the current pandemic crisis.
00:19:57,000 --> 00:20:00,000
And I think that that really will change a lot of the things that we're thinking about.
00:20:00,000 --> 00:20:05,000
In particular, you look at things like slack channels for technology.
00:20:05,000 --> 00:20:09,000
Conferences have always been very popular, but.
00:20:09,000 --> 00:20:14,000
It's going from that being a kind of adjacent thing to the event, to being that is the event.
00:20:14,000 --> 00:20:17,000
You know, video conferencing again. It's not like that's a new technology,
00:20:17,000 --> 00:20:24,000
but the way that people get comfortable with using those things in particular in large groups is going to be really interesting.
00:20:24,000 --> 00:20:31,000
I think how people understand the visual and audio cues that they're getting on multiple person calls is going
00:20:31,000 --> 00:20:37,000
to be interesting because you often have these kind of slightly weird signals where if you were in person.
00:20:37,000 --> 00:20:42,000
So, of course, you know, we're probably sitting about four or five feet apart as we're recording this podcast.
00:20:42,000 --> 00:20:47,000
And that has a particular kind of etiquette about the way that we do distancing
00:20:47,000 --> 00:20:52,000
But if you're in a video conferencing situation, people often have the camera at a slightly weird distance.
00:20:52,000 --> 00:20:55,000
So you either feel like you're too close or you're too far away.
00:20:55,000 --> 00:21:01,000
And that gives different cues to how you perceive that interaction, where they have the microphone to close it.
00:21:01,000 --> 00:21:05,000
It's like they're breathing on you. I don't know if you've had that experience. I'm sure everyone has.
00:21:05,000 --> 00:21:09,000
And it's that really sets up a very different kind of interaction.
00:21:09,000 --> 00:21:13,000
And I think that as these technologies become ever more ubiquitous,
00:21:13,000 --> 00:21:17,000
people are going to have to be getting better at understanding what those implications
00:21:17,000 --> 00:21:21,000
are of sound and eyesight and what that means for people's comfort level of distancing.
00:21:21,000 --> 00:21:25,000
So that for me, is very fascinating subject right now. Yeah, yeah. There's so much to explore.
00:21:25,000 --> 00:21:29,000
And it's going to be interesting how it develops like over the next couple of months especially.
00:21:29,000 --> 00:21:35,000
Definitely. And you mentioned that he thought networking would be particularly with people in the early
00:21:35,000 --> 00:21:41,000
stage of their PhD just in terms of finding out about what different entities are doing,
00:21:41,000 --> 00:21:42,000
how things are moving and trends,
00:21:42,000 --> 00:21:48,000
and then they can use that to think about what skills do I need to pick up and develop and see if someone was interested
00:21:48,000 --> 00:21:55,000
in doing the kind of work that you do like as a digital anthropologist and all the various things that that's include
00:21:55,000 --> 00:22:01,000
What kinds of experiences would be useful for people to try and pick up alongside or as part of the PhD
00:22:01,000 --> 00:22:05,000
I think one of the it's important to focus on one of the reasons that I think it's important
00:22:05,000 --> 00:22:09,000
to do this early in your academic career is because when you are working in academia,
00:22:09,000 --> 00:22:14,000
unless you are doing something part time or you have prior experience outside of academia,
00:22:14,000 --> 00:22:19,000
the people who are teaching you so often don't have the experience of working outside of academia.
00:22:19,000 --> 00:22:25,000
So they are simply not in a very good position to advise you about if you want to explore non-academic options.
00:22:25,000 --> 00:22:28,000
What that transition looks like, what kinds of skills are being looked for.
00:22:28,000 --> 00:22:33,000
They can't really advise you on the kind of non-academic lingo unless they themselves are also doing some of this stuff.
00:22:33,000 --> 00:22:35,000
This is all, of course, very context dependent.
00:22:35,000 --> 00:22:39,000
You have some departments who are very different or you have university support services which can help you.
00:22:39,000 --> 00:22:46,000
But in general, my experience when I was a PhD student was that of many others that I spoke to was that they simply weren't
00:22:46,000 --> 00:22:55,000
able to bridge that gap into the commercial realm because they didn't have the right advice at the time.
00:22:55,000 --> 00:22:59,000
And being an anthropologist and someone who does a lot of ethnography
00:22:59,000 --> 00:23:05,000
I always think that the best way of learning about something is going to immerse yourself in that thing and then experiencing it for yourself.
00:23:05,000 --> 00:23:12,000
So finding an internship or some kind of work experience, I know it's less common for older people to be doing those.
00:23:12,000 --> 00:23:20,000
But you can usually find something. And there are often places that will offer short work placements even to postgraduate students,
00:23:20,000 --> 00:23:26,000
although it is you know, sometimes they're not quite very well set up for that. But, you know, there are definitely places that are doing it,
00:23:26,000 --> 00:23:29,000
especially if they're interested either in your area of research or the kinds of creative skills that
00:23:29,000 --> 00:23:35,000
you can bring to the situation that you're looking at and doing those fairly early on in your career.
00:23:35,000 --> 00:23:42,000
Gives you an opportunity to understand more about yourself, what you like and what you don't like instead of waiting until the end and thinking, hey,
00:23:42,000 --> 00:23:48,000
I'm just going to sit out in the wide world and having this wonderful badge of my degree is going to
00:23:48,000 --> 00:23:55,000
tell people something about who I am and the kind of skills I have often in a commercial setting.
00:23:55,000 --> 00:24:03,000
You know, you might recognise the value of a PhD, but you won't understand how that applies to your business.
00:24:03,000 --> 00:24:09,000
So particular for early people who are just out of the PhD
00:24:09,000 --> 00:24:16,000
It's a hard sell because in essence, from an employer perspective, they're seeing it was just a regular graduate who is a little bit more expensive.
00:24:16,000 --> 00:24:18,000
And that can be challenging to overcome that.
00:24:18,000 --> 00:24:27,000
You know, I'd say after your first job or first couple of jobs, when you move it to either a more managerial role or more strategic looking role,
00:24:27,000 --> 00:24:33,000
then people begin to value your active experience more than they did when you were first out of the gate.
00:24:33,000 --> 00:24:37,000
So that's really tough because that's kind of the biggest hurdle is is getting into your first job.
00:24:37,000 --> 00:24:46,000
It's a very much kind of a catch 22 situation. But coming in from your your postgraduate experience, having had some commercial experience as well,
00:24:46,000 --> 00:24:52,000
puts you in a much stronger position than to be looking at a commercial role because people can
00:24:52,000 --> 00:24:57,000
people make assumptions about your commercial experience when they're reviewing your CV or your,
00:24:57,000 --> 00:25:03,000
you know, as you're being in your hiring process than they will about someone who's just coming with no experience.
00:25:03,000 --> 00:25:08,000
That's obvious to them. Yeah. So it sounds like it's really important.
00:25:08,000 --> 00:25:16,000
First, few roles to really think to really keep in mind that someone else won't know, understand what a PhD is.
00:25:16,000 --> 00:25:21,000
Also all the skills involved. So you really have to work at both getting other experiences,
00:25:21,000 --> 00:25:27,000
maybe then also how you kind of market those things, I guess what those skills mean from your PhD.
00:25:27,000 --> 00:25:31,000
It's not just I did this degree and there's nothing about it that makes sense.
00:25:31,000 --> 00:25:39,000
Yeah. Yeah. Yeah. And also, it's worth remembering that in a commercial setting, the word research can mean very different things.
00:25:39,000 --> 00:25:47,000
So I'm doing some doing a little bit of research on what is the commercial we're looking for and what do those kinds of roles do.
00:25:47,000 --> 00:25:55,000
And if I'm if I'm right. Gosh, the PGR resource that I'm forgetting the name of.
00:25:55,000 --> 00:25:59,000
But it's like academia to ac-doc or something like that. Yeah.
00:25:59,000 --> 00:26:02,000
I can find it to be linked. That would be awesome. Thank you. So.
00:26:02,000 --> 00:26:06,000
So there's some good kind of role descriptions of, you know, what does a U x designer do.
00:26:06,000 --> 00:26:10,000
And what does a commercial analyst do.
00:26:10,000 --> 00:26:14,000
And things of that nature that are just kind of general descriptions of jobs that are out there in
00:26:14,000 --> 00:26:20,000
the market and getting an understanding of what the language is that's used around those roles is
00:26:20,000 --> 00:26:25,000
really helpful because you can then tailor your CV to reflect those skills specifically and in
00:26:25,000 --> 00:26:31,000
particular to take some projects that you've done and demonstrate how those skills relate to that role.
00:26:31,000 --> 00:26:35,000
So essentially, it means you as the person coming into the job,
00:26:35,000 --> 00:26:41,000
you have to be a bit more forward stepping and thinking to to to the commercial
00:26:41,000 --> 00:26:46,000
person to give them an understanding of what you want them to see about that.
00:26:46,000 --> 00:26:49,000
That relates to their job that they have on the market.
00:26:49,000 --> 00:26:55,000
And that can be challenging because, again, sometimes the language is, you know, very jargonistic in particular.
00:26:55,000 --> 00:27:00,000
And, you know, if you've worked in a commercial setting, you might understand the particularities of what they're looking for.
00:27:00,000 --> 00:27:04,000
Whereas if you haven't, you don't really know what they're looking for.
00:27:04,000 --> 00:27:08,000
But trying to get informal interviews with people just to understand what they're specifically
00:27:08,000 --> 00:27:12,000
asking or getting in examples of prior work that other people who are in that field have done.
00:27:12,000 --> 00:27:19,000
So that's why networking isn't just about learning from people who are already hiring managers.
00:27:19,000 --> 00:27:24,000
It's not just about trying to find people who are looking for, you know, who have jobs on offer,
00:27:24,000 --> 00:27:29,000
but also about meeting people in those roles and finding out what their backgrounds are and how they got into that role.
00:27:29,000 --> 00:27:35,000
So it's really important, even just pure networking, can be super important to to understand how they bridge that gap and how they got into that space.
00:27:35,000 --> 00:27:41,000
Yes, I say there's a lot to do in terms of not having assumptions yourself.
00:27:41,000 --> 00:27:45,000
Someone else will understand what you're talking about then not assuming that
00:27:45,000 --> 00:27:48,000
you also know what they're talking about when they say research and you say, I've done this research,
00:27:48,000 --> 00:27:52,000
you might be talking about two completely different things and you might not either
00:27:52,000 --> 00:27:57,000
have a good match or they might not realise that you might be a good match. And talking to other people,
00:27:57,000 --> 00:28:03,000
who are in the field and their experiences can really help to sort of reach those gaps and find that language like you say,
00:28:03,000 --> 00:28:08,000
before you're fully immersed in whatever field. Is that kind of thing.
00:28:08,000 --> 00:28:17,000
Yeah. Yeah. Precisely. Yeah. So you say if someone was applying to work with you with that particular things that you are looking for in
00:28:17,000 --> 00:28:23,000
terms of how people put those things across or things you'll particularly like not looking for things like,
00:28:23,000 --> 00:28:27,000
nope, don't do that. Yeah. Let me answer that question in two ways.
00:28:27,000 --> 00:28:31,000
So where I work now, we are essentially a small consortium of researchers who have very different skills.
00:28:31,000 --> 00:28:37,000
So you can think about in an academic setting as being like an area skills department where you might have an economist and an anthropologist
00:28:37,000 --> 00:28:44,000
and a musicologist and whoever else that are all working on either a particular geographic region or some kind of conceptual region.
00:28:44,000 --> 00:28:47,000
But they all have very, very different skills that they're bringing to the table.
00:28:47,000 --> 00:28:53,000
And they might not even work very closely together, although they might on some projects. So that's really where I work now, is like that.
00:28:53,000 --> 00:28:57,000
We all have very specialised skills. I'm the only digital anthropologist on the team.
00:28:57,000 --> 00:29:04,000
The other people who have more skills that are focussed on looking at things like digitisation and cloud
00:29:04,000 --> 00:29:14,000
technologies and organisational strategy and some in some cases software engineering concepts and things like that.
00:29:14,000 --> 00:29:17,000
So we all have very, very different goals.
00:29:17,000 --> 00:29:23,000
So when we look for someone, we're typically looking for someone who has different skills and what we already have.
00:29:23,000 --> 00:29:34,000
I would say in the roles that we're doing, if I was hiring someone to be an assistant to me, then I probably would be looking for.
00:29:34,000 --> 00:29:37,000
Usually I've done that in a kind of short term project way.
00:29:37,000 --> 00:29:44,000
So in that case, it will very much depend on other project is when we hire into the the LEF.
00:29:44,000 --> 00:29:49,000
More broadly, we probably will be looking for somebody with a fair amount of commercially experience already.
00:29:49,000 --> 00:29:53,000
So I probably wouldn't see that as a good was a good starting role for somebody who has a PhD.
00:29:53,000 --> 00:30:03,000
But, you know, I've managed to make it there eventually. So I think if you want to work in an organisation that's like the one that ours is,
00:30:03,000 --> 00:30:08,000
then it's a matter of figuring out what kinds of steppingstones you need to put him.
00:30:08,000 --> 00:30:10,000
Along the way to get there.
00:30:10,000 --> 00:30:20,000
So to answer the question more from the perspective of my old job, when I was doing a more kind of data science y data analysis, background.
00:30:20,000 --> 00:30:30,000
When we were first hiring people who were typically coming straight out of their degrees for junior analyst roles.
00:30:30,000 --> 00:30:32,000
That was a very quantitatively oriented department.
00:30:32,000 --> 00:30:42,000
So we were typically looking for some examples of statistical knowledge, some potentially familiarity with statistical package software.
00:30:42,000 --> 00:30:47,000
And interestingly, there's not a lot of crossover between academic usage of those things.
00:30:47,000 --> 00:30:53,000
So you typically might be doing SPSS or quite a lot of stuff with, ah, potentially some stuff with Python.
00:30:53,000 --> 00:30:57,000
And what commercial organisations use in those spaces.
00:30:57,000 --> 00:31:01,000
Obviously all the maths is the same, but they simply are using different kinds of software packages.
00:31:01,000 --> 00:31:06,000
So we wouldn't always be looking for some experience in those commercial packages,
00:31:06,000 --> 00:31:14,000
which are things like Tableau and Click View and software package called Looker.
00:31:14,000 --> 00:31:18,000
But if they had some, that was usually perceived as an advantage.
00:31:18,000 --> 00:31:26,000
But if they had Python, our other stuff, we knew that they'd worked with statistical package software before and that was OK.
00:31:26,000 --> 00:31:35,000
We also were looking for people who at the time, again, very quantitive were all but we wanted people who could look at a set of data
00:31:35,000 --> 00:31:39,000
and see where there were irregularities or unusual things happening so that
00:31:39,000 --> 00:31:48,000
they could then raise a challenge in terms of either how the data was being collected or an anomaly of some kind in what was happening with the data.
00:31:48,000 --> 00:32:01,000
So you needed to have a bit of an investigative hat. And I would say my role there as an anthropologist was much more about assisting
00:32:01,000 --> 00:32:06,000
people with the kind of more ephemeral qualities of questioning those things.
00:32:06,000 --> 00:32:15,000
So while I did have a very quantitative role when I was there, I wasn't necessarily doing a lot of the kind of data sciences side of things.
00:32:15,000 --> 00:32:20,000
A lot of it was more of the summary statistics. And then, OK, we've noticed that there's an unusual pattern.
00:32:20,000 --> 00:32:23,000
What are some creative ideas we can think about, about in terms of why that might be?
00:32:23,000 --> 00:32:29,000
So you needed that mixture of people who could do the the crunchier side of the maths,
00:32:29,000 --> 00:32:39,000
but also say things like all the schools are on holiday this week or there's been a strike in Chicago teaching in the Chicago teaching union
00:32:39,000 --> 00:32:46,000
And so therefore, we're having less people who are logging on to share their stories with us this week or whatever it might be.
00:32:46,000 --> 00:32:53,000
So there is kind of that social side in terms of understanding what you know, if you see something unusual, what might it be?
00:32:53,000 --> 00:32:59,000
So a lot of my role in the end was really about training the newer trainees so they would come in with a more kind of hard sciences background.
00:32:59,000 --> 00:33:05,000
And then my role would be to help them. Question. When you see something unusual, why might that be so they can answer a lot of questions about this.
00:33:05,000 --> 00:33:09,000
Looks weird, but they didn't necessarily know what to do with that information. And my role is to help them understand that.
00:33:09,000 --> 00:33:12,000
Know how could you then question this more broadly? Yeah.
00:33:12,000 --> 00:33:18,000
So it's kind of, um, combining those that kind of hard science, the social sciences types together.
00:33:18,000 --> 00:33:25,000
Precisely. And I would say if you depending on the size of the organisation you're with, you often find that you get blended teams.
00:33:25,000 --> 00:33:31,000
So and that can be a real strength when you're able to when you're able to have people who have strengths in different areas,
00:33:31,000 --> 00:33:37,000
it allows you to see information in a different way than if you are just one person is looking at it in one way.
00:33:37,000 --> 00:33:42,000
And of course, there's always the wonderful idea of having everyone have all of the skills.
00:33:42,000 --> 00:33:44,000
But people are simply going to have different strengths.
00:33:44,000 --> 00:33:48,000
And recognising where they can contribute the most is really important for any organisation to do.
00:33:48,000 --> 00:33:56,000
Yeah. Yeah, sure. I know I say sounds like you're saying your current role and maybe that's a person that's listenings dream.
00:33:56,000 --> 00:34:03,000
Well, they want to work in a team, but it's a case that you won't necessarily do that straight away to think about the kind of work.
00:34:03,000 --> 00:34:08,000
What are the steps and experiences I need to get to that point. If that's the kind of thing I want to be aiming for.
00:34:08,000 --> 00:34:12,000
Yeah. Precisely. So a good example would be like, there is no way that I would have the job I have now,
00:34:12,000 --> 00:34:15,000
even though my role is much more qualitative than it was previously.
00:34:15,000 --> 00:34:21,000
If I hadn't had my experience where I was doing essentially the kind of hard number crunching for the past six years before that,
00:34:21,000 --> 00:34:26,000
because it gave me experiences like managing a team, give me a lot of organisational operational experience.
00:34:26,000 --> 00:34:32,000
So I understood the different parts of what most businesses have in terms of the kinds of ways that they're set up.
00:34:32,000 --> 00:34:39,000
Give me a lot of experience around kind of standard ways of doing commercial modelling for different kinds of things.
00:34:39,000 --> 00:34:45,000
So then when I go into businesses now where where I'm advising them, I usually understand the organisational setup pretty well.
00:34:45,000 --> 00:34:53,000
Because, you know, though, of course, there are differences, there are definitely commonalities in terms of how large organisations are always set up.
00:34:53,000 --> 00:34:55,000
So if I hadn't had that experience,
00:34:55,000 --> 00:35:01,000
I wouldn't simply I've simply wouldn't be able to kind of stretch to putting myself in the shoes of the organisations I work with.
00:35:01,000 --> 00:35:08,000
So so, yeah, it's definitely that kind of sense of, OK, if I want to someday work in a think tank or work in a research.
00:35:08,000 --> 00:35:15,000
organisation or something of that nature or go into a kind of political policy organisation.
00:35:15,000 --> 00:35:17,000
What do I need to do so that when I get there,
00:35:17,000 --> 00:35:25,000
I have the right mixture of skills and background and essentially area knowledge so that I can really provide the most value in that kind of role.
00:35:25,000 --> 00:35:33,000
Yeah, yeah. And when you were moving to your first role at tes, like, how did you find because obviously that was quite different in terms of quantitative,
00:35:33,000 --> 00:35:39,000
in terms of applying for that role, how you sort of sold your skills in that setting mixture thing.
00:35:39,000 --> 00:35:43,000
So I had applied for several different things around that time.
00:35:43,000 --> 00:35:49,000
I specifically remembers applying for internship and publishing as well. And I was applying at that time as well as it has.
00:35:49,000 --> 00:35:55,000
And the tes connection was actually through a personal friend.
00:35:55,000 --> 00:36:02,000
So, again, networking, it comes down to, you know, it absolutely is about what you know, because, you know,
00:36:02,000 --> 00:36:07,000
when you show up in the room to be the one who is in the interview, you have to you have to pass the bar.
00:36:07,000 --> 00:36:13,000
But in terms of the knowledge about what roles are available and out there,
00:36:13,000 --> 00:36:19,000
it really is helpful to not just be depending on job boards and kind of publicly available information.
00:36:19,000 --> 00:36:27,000
Having some knowledge about, you know, roles that either are not being advertised explicitly or in particular this role.
00:36:27,000 --> 00:36:31,000
When I first was applying, it has had a very hard time filling the role.
00:36:31,000 --> 00:36:35,000
And that's partly because it was a slightly unusual setup for the role.
00:36:35,000 --> 00:36:42,000
So a lot of the people that they were interviewing either had one side of the job that they were looking for covered already,
00:36:42,000 --> 00:36:44,000
or they had the other side that they wanted.
00:36:44,000 --> 00:36:53,000
So in this case, they wanted somebody who could do a lot of the kind of analysis and Day-To-Day reporting.
00:36:53,000 --> 00:37:00,000
But they also wanted someone who they could eventually train to do some of the the actual programming of the reporting tools.
00:37:00,000 --> 00:37:04,000
And what they were finding at the time was that they could they could find someone who was one of the other very strongly,
00:37:04,000 --> 00:37:10,000
who had a commercial background. But they were really struggling to find somebody who either had both or wanted to do both because it was unusual,
00:37:10,000 --> 00:37:17,000
you know, expectation, especially for that level of role. And of course, I come in as a newly graduated PhD and like, I can do anything.
00:37:17,000 --> 00:37:23,000
I'm willing to do whatever it takes to succeed in this job. And sometimes that extra flexibility of simply saying, hey,
00:37:23,000 --> 00:37:31,000
I'm willing to learn it can it can sometimes put you in a better position simply because other people whose careers were
00:37:31,000 --> 00:37:40,000
fixed or have a very focussed career path in mind might not be interested in having that kind of broad range of skills.
00:37:40,000 --> 00:37:48,000
And so, you know, for you to come in then and say, I can learn things very quickly and I'm very experienced in part of this or I am
00:37:48,000 --> 00:37:51,000
very thorough in the way that I go about learning things can be a real advantage.
00:37:51,000 --> 00:37:56,000
And so that was eventually what happened was because they'd had such a hard time filling the role,
00:37:56,000 --> 00:38:01,000
they were then willing to look slightly differently at what kinds of mix of skills they needed. So essentially,
00:38:01,000 --> 00:38:10,000
I showed up at the right time when they were looking for someone who is a little bit different than what they had initially had in mind.
00:38:10,000 --> 00:38:14,000
And then when I was doing the interviewing, clearly they were impressed by the research skills that I had,
00:38:14,000 --> 00:38:21,000
but also some of the ways that I was thinking about or questioning some of the stuff that they were putting forward that made them feel like,
00:38:21,000 --> 00:38:26,000
OK, this could be someone who can approach this role differently, which is really helpful for them.
00:38:26,000 --> 00:38:31,000
And interestingly enough, when I went to then move to the leading edge forum where I work now,
00:38:31,000 --> 00:38:35,000
I knew that I was ready to move on from a role that was very quantitative.
00:38:35,000 --> 00:38:38,000
And I wanted to get back into some of those more kind of core research skills that I developed.
00:38:38,000 --> 00:38:45,000
And when I was here at Exeter and I was having a hard time because my role at that point was so quantitive that all anyone could see in me was,
00:38:45,000 --> 00:38:51,000
oh, she's an analyst. She's an analyst. And so it was very hard for them to see that the qualitative skills that I'd amassed
00:38:51,000 --> 00:38:55,000
in the previous simply weren't things that in their mind were showing up for them.
00:38:55,000 --> 00:38:57,000
When I was trying to put myself forward.
00:38:57,000 --> 00:39:05,000
So but the leading edge forum was specifically looking for someone who wanted to do a digital anthropology programme for them, programme of research.
00:39:05,000 --> 00:39:09,000
So again, it was just the right thing at the right time. It just matched up. That was what I wanted to do and that was what they needed.
00:39:09,000 --> 00:39:14,000
And again, they'd been having a hard time filling the role because they had a lot of people who either had a
00:39:14,000 --> 00:39:19,000
lot of commercial experience but didn't really have the kind of core research skills that I had.
00:39:19,000 --> 00:39:25,000
Or they had a lot of people who had been doing very academic research for a long time,
00:39:25,000 --> 00:39:31,000
but didn't have the commercial experience and the context to operate in that world.
00:39:31,000 --> 00:39:36,000
So, you know, it's just about finding the right the right match at the right moment, I think.
00:39:36,000 --> 00:39:41,000
Yeah. Yeah. And this only about. Throughout kind of the importance of networking,
00:39:41,000 --> 00:39:47,000
finding out about jobs that are available in any kind of different people's experience and backgrounds in these industries.
00:39:47,000 --> 00:39:52,000
And it sounds like that makes it experience between the academic and the kind
00:39:52,000 --> 00:39:57,000
of commercial industry industry type stuff and get having both those things.
00:39:57,000 --> 00:40:02,000
And I said maybe trying to get some of these experiences durinf your PhD really helpful.
00:40:02,000 --> 00:40:06,000
Yeah, yeah, absolutely. It can be really powerful if you want to move into a commercial role.
00:40:06,000 --> 00:40:17,000
And I I'd say also what I've observed. Is there an increasing number of public private partnerships or academic quasi
00:40:17,000 --> 00:40:24,000
academic research skills or or things of that nature where there's some kind of,
00:40:24,000 --> 00:40:32,000
oh, hey, we, the university have a lot of research skills or a lot of scope for doing like innovation lab style stuff.
00:40:32,000 --> 00:40:34,000
But what we don't have is a lot of the commercial side of things.
00:40:34,000 --> 00:40:42,000
So they develop these like digital hubs or innovation hubs in different parts of the world, in different country.
00:40:42,000 --> 00:40:51,000
And so there are often roles that are available that are kind of quasi academic, but also really depend on the commercial experience as well.
00:40:51,000 --> 00:40:54,000
So, you know, I haven't really had an experience of fighting for those,
00:40:54,000 --> 00:40:58,000
but it's something I've observed as I've been thinking about my my future career path.
00:40:58,000 --> 00:41:02,000
It's something that I've observed is out there in the market. So there might be something like that. You know,
00:41:02,000 --> 00:41:05,000
if you're thinking about perhaps wanting to stick a bit closer on the academic
00:41:05,000 --> 00:41:10,000
side and maintaining those academic credentials and publishing and all that.
00:41:10,000 --> 00:41:16,000
But also having a bit of commercial experience that would let you be that kind of linchpin between those two those two things.
00:41:16,000 --> 00:41:23,000
So I'd say that's an interesting potential career path as well. It's adjacent to but not exactly the same as the way that I've gone.
00:41:23,000 --> 00:41:27,000
And would there be any other kind of final tips you'd give someone kind of in the middle of
00:41:27,000 --> 00:41:33,000
your PhD or something you wish you'd done a bit differently when you were doing your PhD?
00:41:33,000 --> 00:41:36,000
I think the only other tip.
00:41:36,000 --> 00:41:45,000
And again, it's probably something that is spoken about perhaps a bit more than when I was a student, is prioritising your own self care.
00:41:45,000 --> 00:41:51,000
And I mean that not in a fluffy bubble bath kind of way, although if that is something that works for you, then great.
00:41:51,000 --> 00:41:57,000
But really look after your own mental health and your own physical health.
00:41:57,000 --> 00:42:05,000
Because if you don't have a working as a working instrument, then it's going to be very difficult for you to play the sonata, basically.
00:42:05,000 --> 00:42:15,000
And I'm hoping that there are a lot of resources out there available now to enable students to to really
00:42:15,000 --> 00:42:22,000
care about those things and to look after themselves and also to develop those habits early in life,
00:42:22,000 --> 00:42:24,000
especially when you're in the kind of pressured environment that a Masters or
00:42:24,000 --> 00:42:30,000
PhD is that will put you in extremely good stead for later in life when you
00:42:30,000 --> 00:42:34,000
have pressured roles or are dealing with different kinds of pressures like
00:42:34,000 --> 00:42:38,000
balancing work and family or what or financial concerns or whatever it might be.
00:42:38,000 --> 00:42:46,000
So developing those habits early on, when you're at what might be the most pressured moment of your career, ultimately will then help you.
00:42:46,000 --> 00:42:52,000
Everything else beyond that will seem like a piece of cake then. And that's it for this episode.
00:42:52,000 --> 00:43:07,349
Join us next time when we'll be talking to another researcher about their career beyond their research degree.