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 Kelly Preece, Researcher Development Manager talks to Dr. Denise Wilkins, Researcher at Microsoft Research.

Music from https://filmmusic.io ’Cheery Monday’ by Kevin MacLeod (https://incompetech.com) License: CC BY (https://creativecommons.org/licenses

Podcast transcript

1 00:00:10,000 --> 00:00:15,000 Hello and welcome to the Beyond Your Research Degree podcast by the University of Exeter Doctoral College

2 00:00:15,000 --> 00:00:28,000 It's Kelly Preece here research development manager ing the University of Exeter Doctor College.

3 00:00:28,000 --> 00:00:30,000 And I'll be your host for this episode.

4 00:00:30,000 --> 00:00:40,000 I'm delighted to be talking to another University of Exeter doctoral alumnus, Denise Wilkins, who is currently working as a researcher in industry.

5 00:00:40,000 --> 00:00:50,000 Denise, are you happy to introduce yourself, I'm Denise Wilkins and I'm a social scientist and I work at Microsoft Research in Cambridge.

6 00:00:50,000 --> 00:01:00,000 So my job there really is to conduct research. So I'll be trying to understand people.

7 00:01:00,000 --> 00:01:06,000 Social scientists trying to understand their needs and really try to feed insights back

8 00:01:06,000 --> 00:01:13,000 to people who are looking at the future of technology development to really think how,

9 00:01:13,000 --> 00:01:22,000 you know, what I'm hearing, what I'm talking to, people might translate and be applied to products that we might want to develop in the longer term.

10 00:01:22,000 --> 00:01:27,000 And so at the moment, we're working in a theme called The Future of Work.

11 00:01:27,000 --> 00:01:35,000 So we're really interested to understand what the work might look like in the future and how technology might support that.

12 00:01:35,000 --> 00:01:40,000 And my project is looking at knowledge in large organisations, say,

13 00:01:40,000 --> 00:01:49,000 trying to find ways to help workers in large organisations share knowledge and have knowledge kind of more available to them in their work.

14 00:01:49,000 --> 00:01:56,000 What was your research degree in at Exeter? My degree was in psychology.

15 00:01:56,000 --> 00:01:59,000 Say it was it was very kind of similar themes.

16 00:01:59,000 --> 00:02:09,000 I was looking at technology and in particular I was looking at a social media and how it might affect people's willingness to engage in activism.

17 00:02:09,000 --> 00:02:15,000 So to put it, I was really inspired by things like the Arab Spring and where you might have

18 00:02:15,000 --> 00:02:20,000 seen or have kind of had news stories that social media played a role in,

19 00:02:20,000 --> 00:02:29,000 acts as a catalyst by inspiring people to go on the streets. But at the same time, there was also kind of a slacktivism narrative going on which said,

20 00:02:29,000 --> 00:02:33,000 well, you know, people are just like him things and sharing things on social media.

21 00:02:33,000 --> 00:02:37,000 And they're not really kind of going on the ground and doing the hard effort. So really

22 00:02:37,000 --> 00:02:45,000 Well, what I tried to do in my PhD was to really understand when and how social media might facilitate activism

23 00:02:45,000 --> 00:02:51,000 and social change and what are the type of circumstances where it might maybe have a different effect.

24 00:02:51,000 --> 00:02:59,000 And reduce people's willingness to do that. On what? When might it have more kind of negative effects and social change?

25 00:02:59,000 --> 00:03:02,000 So although I was in psychology,

26 00:03:02,000 --> 00:03:09,000 my research will always have the interest in people and technology and how technology can be a positive driver for change.

27 00:03:09,000 --> 00:03:18,000 And that's kind of followed me on to my work at Microsoft. So I'm interested to know what what your plan was, I guess,

28 00:03:18,000 --> 00:03:25,000 when you were doing the coming to the end of your research degree in the write-up, which is incredibly challenging in and of itself.

29 00:03:25,000 --> 00:03:33,000 Did you have a clear plan of what you wanted to do afterwards? Was the plan always to go into a research career in industry?

30 00:03:33,000 --> 00:03:36,000 Yeah. Well, at the time, I don't think I was aware.

31 00:03:36,000 --> 00:03:40,000 of the different options and career paths that there were.

32 00:03:40,000 --> 00:03:46,000 And I knew that I love researching. I knew that I love talking to people.

33 00:03:46,000 --> 00:03:49,000 And I knew that I wanted to have an impact, say,

34 00:03:49,000 --> 00:03:56,000 thinking about how technology so pervasive in our everyday lives and how new technology is being created all the time.

35 00:03:56,000 --> 00:04:04,000 I was aware that, you know, that there are kind of negative impacts that technology can have, say how can.

36 00:04:04,000 --> 00:04:08,000 And so the idea as a researcher take a role in shaping that.

37 00:04:08,000 --> 00:04:12,000 And I wasn't really sure then about the opportunities that existed in industry.

38 00:04:12,000 --> 00:04:19,000 It wasn't something that I heard much about. You know, psychology's part of STEM in Exeter.

39 00:04:19,000 --> 00:04:28,000 So I often heard about people with like a chemistry or biology degrees and how they might go to kind of pharmaceutical companies.

40 00:04:28,000 --> 00:04:35,000 But I didn't really hear much of the narrative about what kind of psychology PhD could do with their degree.

41 00:04:35,000 --> 00:04:44,000 So I wasn't really aware and I was mostly looking for the kind of jobs in academia and postdocs in academia.

42 00:04:44,000 --> 00:04:50,000 And I actually I went on. And prior to working in Microsoft, I did a postdoc and I Exeter.

43 00:04:50,000 --> 00:04:54,000 So that was with the same P.I.

44 00:04:54,000 --> 00:05:00,000 He supervised me for my PhD. And that was looking at a different form of technology in different contexts.

45 00:05:00,000 --> 00:05:07,000 And I was looking at block chain and how and how it could be used to create new peer-to-peer energy markets.

46 00:05:07,000 --> 00:05:14,000 I was looking at the energy sector there. It was only when I started doing that postdoc

47 00:05:14,000 --> 00:05:22,000 One of the other researchers on the same project really told me about kind of user research.

48 00:05:22,000 --> 00:05:32,000 They told me about HCI as a field. And they told me about my research in Cambridge and how they do lots of they have lots of engagement,

49 00:05:32,000 --> 00:05:39,000 kind of which social science and which social scientists that there really is a role for kind of social scientists in large

50 00:05:39,000 --> 00:05:48,000 organisations like that and engaging with different users and generating insights that can be used by design and developers.

51 00:05:48,000 --> 00:05:49,000 So was that an immediate move?

52 00:05:49,000 --> 00:05:55,000 So when you finished your postdoc, did you go straight to a job at Microsoft Research or was there something in between?

53 00:05:55,000 --> 00:06:01,000 Yeah, there wasn't anything in between. So from talking to her it just sounded really inspirational

54 00:06:01,000 --> 00:06:05,000 It sounded kind of exactly what I wanted to do

55 00:06:05,000 --> 00:06:18,000 So no, on the one hand and. So Microsoft research is slightly different from like Microsoft, so there's kind of two arms to Microsoft.

56 00:06:18,000 --> 00:06:25,000 You have sort of Microsoft and the product groups and they'd be directly they still do user research

57 00:06:25,000 --> 00:06:31,000 and they and they would be directly trying to impact the products we use every day in the short term.

58 00:06:31,000 --> 00:06:42,000 So it really is. As far as I totally understand that it's about sort of what really focussed on finding insights that can improve specific products.

59 00:06:42,000 --> 00:06:48,000 Whereas Microsoft Research has its longer term or indeed vision.

60 00:06:48,000 --> 00:07:00,000 So I'm not part of any particular project, product group, but I hope to have insights that could perhaps impact and shape any of the products.

61 00:07:00,000 --> 00:07:04,000 And other large tech companies have similar.

62 00:07:04,000 --> 00:07:09,000 You have Google and you've got Google product groups, but you will see what people research.

63 00:07:09,000 --> 00:07:13,000 So, yeah, that's that's kind of one of the splits that you have.

64 00:07:13,000 --> 00:07:23,000 So really what I liked about Microsoft research is that you have the opportunity to have the real world impact on the products.

65 00:07:23,000 --> 00:07:29,000 And by really doing that I'm aiming for that kind of thought leadership and find it,

66 00:07:29,000 --> 00:07:37,000 finding these insights that can impact the longer term vision that there really is this kind of academic community.

67 00:07:37,000 --> 00:07:43,000 So we're encouraged to write publications and to submit them to journals and to conferences.

68 00:07:43,000 --> 00:07:48,000 Really, really there is this academic engagement.

69 00:07:48,000 --> 00:07:58,000 We also have. So that's another reason why that's those kind of opportunities with Microsoft Research really appealed

70 00:07:58,000 --> 00:08:05,000 to me because I felt like it ticked both of the boxes of what I really loved about being in academia.

71 00:08:05,000 --> 00:08:14,000 So on the one hand, trying to have real world impact or say being part of a broader academic and scientific community where you're able to sort of

72 00:08:14,000 --> 00:08:21,000 push your learnings out more broadly and beyond kind of the immediate project that you might be working on through publications,

73 00:08:21,000 --> 00:08:27,000 for example. Yes, and what you're saying about not being aware of the opportunities in industry,

74 00:08:27,000 --> 00:08:36,000 but particularly where social science type research might be happening in industry is something we hear a lot for from students.

75 00:08:36,000 --> 00:08:44,000 So from what you're saying, it sounds like there were a lot of similarities between the role that you're doing now and a research role in academia.

76 00:08:44,000 --> 00:08:51,000 So could you talk a little bit about what the differences are? So what's different about researching in industry compared to academia?

77 00:08:51,000 --> 00:09:00,000 Yeah. So I think, you know, one of those pieces that I like, which is much stronger is is the impact.

78 00:09:00,000 --> 00:09:13,000 Say, I feel like maybe for me as a junior researcher in a university, that idea of impact was probably quite far from my mind.

79 00:09:13,000 --> 00:09:18,000 So I want to see the research I wanted to write out for publication.

80 00:09:18,000 --> 00:09:23,000 And then you heard stories about people talking about impact are more senior.

81 00:09:23,000 --> 00:09:30,000 Well, I never really knew what that meant. I didn't really know how I would go about having impact.

82 00:09:30,000 --> 00:09:36,000 And I think sometimes on a personal level, I would think I'm I'm doing research and I'm I'm writing papers.

83 00:09:36,000 --> 00:09:43,000 But who's reading them. Who's going to do something with them.

84 00:09:43,000 --> 00:09:46,000 Is is it other folk from the psychology community, which is great.

85 00:09:46,000 --> 00:09:54,000 But, you know, how can you go beyond your community and and really encourage people who are designing technology to do it differently?

86 00:09:54,000 --> 00:10:01,000 And for me. That was just perhaps a kind of psychological gap in my head,

87 00:10:01,000 --> 00:10:08,000 like I couldn't see how those steps joined up, whereas in my soul, for me, it's much clearer.

88 00:10:08,000 --> 00:10:18,000 And so I'm just a really practical examples. We have regular meetings, we have different product groups, and I'll be sharing my insights with them.

89 00:10:18,000 --> 00:10:23,000 So really, the stakeholders of the research are really clear.

90 00:10:23,000 --> 00:10:31,000 And, you know, you have those in mind when you're trying to design the research and you have the opportunity to really think,

91 00:10:31,000 --> 00:10:35,000 well, how how might this kind of shape shape their thinking?

92 00:10:35,000 --> 00:10:40,000 So that's the kind of steps are a lot clearer to me, which is one thing that I really liked.

93 00:10:40,000 --> 00:10:46,000 I think it perhaps changes some of the type of things you might produce.

94 00:10:46,000 --> 00:10:51,000 So I think sometimes in sort of academia where we're taught to write

95 00:10:51,000 --> 00:10:57,000 Kind of papers and the papers can be really long. And, you know, people are really interested in the details.

96 00:10:57,000 --> 00:11:02,000 So they want to know exactly what methods you used and they'll want to know a

97 00:11:02,000 --> 00:11:08,000 lot about kind of the background and your kind of theoretical justification. And again, I want to know at the end,

98 00:11:08,000 --> 00:11:16,000 how does how what other kind of impacts of this and other academics will really have time to kind of read those long papers.

99 00:11:16,000 --> 00:11:19,000 And we need to still learnings from it.

100 00:11:19,000 --> 00:11:26,000 But I think one of the things in industry is that you're trying to communicate # to lots of different people.

101 00:11:26,000 --> 00:11:29,000 And some people they might be the same specialism as you.

102 00:11:29,000 --> 00:11:33,000 So there might be other social scientists and I might have a lot more time to read all of that.

103 00:11:33,000 --> 00:11:40,000 But you also might be talking to kind of leaders or designers or people need to make that decision about their product really quickly.

104 00:11:40,000 --> 00:11:44,000 So they will just really want to have something that they can absorb like, say,

105 00:11:44,000 --> 00:11:52,000 really a PowerPoint and they just want to know on know even two slides, like what are the key things I need to know?

106 00:11:52,000 --> 00:11:56,000 And so it's about communicating a lot and a lot more kind of concise ways.

107 00:11:56,000 --> 00:12:07,000 And also perhaps not being afraid to have an opinion and how they're a strength and say these are tje recommendations is what I would advise you today.

108 00:12:07,000 --> 00:12:13,000 And again, for me, at least in academia. I felt like that wasn't something that I did before.

109 00:12:13,000 --> 00:12:19,000 I didn't really make lots of presentations, only occasionally of us going to a conference, for example.

110 00:12:19,000 --> 00:12:26,000 And again, I, I think it was just my personality but I would shy away from making really strong recommendations and say,

111 00:12:26,000 --> 00:12:30,000 well, because of this study, we need to be X, Y and Z.

112 00:12:30,000 --> 00:12:33,000 But that's really what people are looking for in industry.

113 00:12:33,000 --> 00:12:38,000 You to give the practical recommendations for that for that work and what they should do next.

114 00:12:38,000 --> 00:12:44,000 So I'm hearing a lot and what you're saying about the core skill set that you use in your current role

115 00:12:44,000 --> 00:12:50,000 and communication in a variety different forms and formats seems to be an important part of that.

116 00:12:50,000 --> 00:13:01,000 But I wonder what other sort of general skills did you learn or develop during your research degree that you use on a daily basis now?

117 00:13:01,000 --> 00:13:14,000 I think because of my degree, I think one of. The core skills that I learnt was really planning research and then sort of learning

118 00:13:14,000 --> 00:13:18,000 how to conduct research on having sort of a variety of different research methods.

119 00:13:18,000 --> 00:13:28,000 So really that kind of expertise with people and being able to interview people and get them to talk to you about whatever,

120 00:13:28,000 --> 00:13:34,000 whatever topic they might they might have and then really been able to put that together into a narrative.

121 00:13:34,000 --> 00:13:45,000 So I feel that's one of kind of the strongest, the strongest skills that I've kind of taken from my PhD

122 00:13:45,000 --> 00:13:49,000 So something that I think would be really interesting for our listeners is that you've

123 00:13:49,000 --> 00:13:55,000 interviewed and been successful for a research job in academia and in industry.

124 00:13:55,000 --> 00:13:59,000 So can you talk about the interview, and application processes for those roles?

125 00:13:59,000 --> 00:14:07,000 And if they were similar or if they were different and if so, what the differences were and they were different.

126 00:14:07,000 --> 00:14:15,000 So the the entry process at Microsoft was much longer.

127 00:14:15,000 --> 00:14:19,000 So there were a number of calls first.

128 00:14:19,000 --> 00:14:32,000 I think first I submitted an application, which was I think it was a CV and maybe maybe a statement, a short statement as to why the job was with.

129 00:14:32,000 --> 00:14:38,000 Interesting. And then I had a call from a recruiter.

130 00:14:38,000 --> 00:14:43,000 He just really wanted to cover some kind of fundamental thing.

131 00:14:43,000 --> 00:14:49,000 So the job I actually have with Microsoft, it is called a postdoc.

132 00:14:49,000 --> 00:14:54,000 So it was just really checking things of, you know, how have I finished my PhD?

133 00:14:54,000 --> 00:15:04,000 And just trying to get the basics to kind of field. And then I was passed on to a telephone interview with the person who is now my manager.

134 00:15:04,000 --> 00:15:10,000 So I think she interviewed me, for about an hour.

135 00:15:10,000 --> 00:15:20,000 And then after that, I got invited to the lab where I would give a presentation, say the presentation was an hour.

136 00:15:20,000 --> 00:15:28,000 And then I had an interviews with one to one interviews with a number of different researchers at the lab.

137 00:15:28,000 --> 00:15:34,000 So it really was like a whole When I was there, it was really like a whole day event, the number of different activities.

138 00:15:34,000 --> 00:15:44,000 Whereas my postdoc, Exeter, I did the I think it was the normal application of the CV and the cover letter.

139 00:15:44,000 --> 00:15:51,000 And then I got invited to an interview and I was interviewed by a panel of three people who ask questions.

140 00:15:51,000 --> 00:15:56,000 And I think, you know, that interview was for less than an hour.

141 00:15:56,000 --> 00:16:02,000 So I think that the length and the number of stages was much different.

142 00:16:02,000 --> 00:16:10,000 And in industry compared to the university, you know, and I think because the task the difference I didn't give a presentation,

143 00:16:10,000 --> 00:16:15,000 was interviewed at the university, say again, that had a different type of preparation.

144 00:16:15,000 --> 00:16:18,000 So I had to kind of put the presentation together.

145 00:16:18,000 --> 00:16:26,000 But I think in terms of like the the fundamental preparation for the interview and thinking, you know, why do you want the job?

146 00:16:26,000 --> 00:16:30,000 Why what have you got to offer? How does that fit into your career path?

147 00:16:30,000 --> 00:16:35,000 Why this organisation? Why this role? And those things were great.

148 00:16:35,000 --> 00:16:43,000 And also say when I was applying for both jobs I got help from the career service at Exeter.

149 00:16:43,000 --> 00:16:49,000 So I had a one to one session with one of the career advisers.

150 00:16:49,000 --> 00:16:58,000 She specifically helps PhD students. And that was really sort of invaluable both times in terms of sort like just helping me think about it.

151 00:16:58,000 --> 00:17:06,000 So I really felt like that kind of preparation that I did beforehand would be really key.

152 00:17:06,000 --> 00:17:14,000 And I would encourage anybody who's applying for any type of job, reallu to put the work into that preparation.

153 00:17:14,000 --> 00:17:22,000 You know, any any might even that work might even span a few days when you go away and you'll really be searching and understanding things.

154 00:17:22,000 --> 00:17:23,000 So, yeah,

155 00:17:23,000 --> 00:17:30,000 I feel like that was something that really helped me with both with being able to do that kind of up from preparation and get my my head into space.

156 00:17:30,000 --> 00:17:34,000 So I need kind of a story that I wanted to tell. Absolutely.

157 00:17:34,000 --> 00:17:41,000 And did you find you articulated that story and those skills differently in the different contexts?

158 00:17:41,000 --> 00:17:45,000 I feel like it was similar. Yeah, I do feel like it was similar.

159 00:17:45,000 --> 00:17:49,000 I think because, you know, the job I have with Microsoft is a postdoc.

160 00:17:49,000 --> 00:17:55,000 So they are expecting somebody. who doesn't have you know

161 00:17:55,000 --> 00:18:02,000 Somebody who i new to industry is somebody who has completed a PhD and they're looking for that kind of first industry position.

162 00:18:02,000 --> 00:18:07,000 So they weren't you we'd expect me to come and say, you know, I've got years of, you know,

163 00:18:07,000 --> 00:18:16,000 working with product groups and, you know, delivering insights and having this massive impact on how organisations run.

164 00:18:16,000 --> 00:18:26,000 And it really was trying to articulate how the findings from kind of my my PhD, for example,

165 00:18:26,000 --> 00:18:34,000 of how some of the findings that I have could be relevant and impactful for them and kind of Microsoft as stakeholders.

166 00:18:34,000 --> 00:18:43,000 What would that look like? And I think that was kind of similar. to my postdoc interview in academia, they really want to kind of, you know,

167 00:18:43,000 --> 00:18:49,000 know some of those kind of transferable skills, so the postdoc that I did at Exeter.

168 00:18:49,000 --> 00:18:52,000 And it was a completely different topic.

169 00:18:52,000 --> 00:19:01,000 But they wanted to able you know what what skills would you bring and how how would she make sure that they that that could benefit all project?

170 00:19:01,000 --> 00:19:04,000 So I feel like that was there were lots of similarities. Yeah.

171 00:19:04,000 --> 00:19:12,000 It sounds like the threads between the different research roles in different contexts are actually really strong.

172 00:19:12,000 --> 00:19:19,000 Can you talk to me a little bit about your average, say? I know there's no such thing as an average day right now,

173 00:19:19,000 --> 00:19:27,000 but how different is you kind of working day and working life to when you were a research degree student and a postdoc?

174 00:19:27,000 --> 00:19:34,000 So I think my average day I'm now in industry is quite different to how it was as a PhD student.

175 00:19:34,000 --> 00:19:41,000 And for me, at least mostly in my PhD, I was really working on on my own.

176 00:19:41,000 --> 00:19:49,000 Say, a lot of the time I was in wasn't meeting with many other people to discuss my research.

177 00:19:49,000 --> 00:19:55,000 Other than my academic supervisors, I'm very rarely.

178 00:19:55,000 --> 00:20:01,000 I would give maybe a presentation to kind of the lab group that we had.

179 00:20:01,000 --> 00:20:09,000 So it really was a very individual work. I felt like I was kind of doing it for myself.

180 00:20:09,000 --> 00:20:15,000 And I also felt like, you know, this is for me when I'm ready to

181 00:20:15,000 --> 00:20:22,000 Share that. When once I got the paper or once I've done the presentation, I'll share that with other people.

182 00:20:22,000 --> 00:20:29,000 But I think the kind of flipside of that was always that question. My model, who's really interested in the in the results of this?

183 00:20:29,000 --> 00:20:36,000 Like, what's going to happen to it later? Whereas in Microsoft, it's much more collaborative.

184 00:20:36,000 --> 00:20:42,000 So I'm working as part of a multidisciplinary team, so there's designers on the team.

185 00:20:42,000 --> 00:20:50,000 And there's machine only researchers and theire's engineers. And we have sort of regular meetings throughout the week.

186 00:20:50,000 --> 00:21:01,000 So in any one day I might be meeting with the team members to tell them about the things I've been doing, so to update on

187 00:21:01,000 --> 00:21:06,000 The things I've been doing during the week, or also to hear about what they've been doing.

188 00:21:06,000 --> 00:21:14,000 I might be helping people conduct their own research, say some of the designers they do research on might be helping them like recruit participants.

189 00:21:14,000 --> 00:21:19,000 I might be helping them think about some of their findings and distil insights.

190 00:21:19,000 --> 00:21:27,000 I might be kind of contributing to a PowerPoint that we're making to show other people the work we've done.

191 00:21:27,000 --> 00:21:32,000 And there is I might be I might be participating in a brainstorm or workshop where we're

192 00:21:32,000 --> 00:21:37,000 trying to understand the next phase of the project and what some of our priorities are.

193 00:21:37,000 --> 00:21:44,000 But there is still space for individual work. So I would still conduct my research studies.

194 00:21:44,000 --> 00:21:52,000 I'd be doing literature reviews. I'd be doing going through an ethics process, say, to get ethical approval for my study.

195 00:21:52,000 --> 00:21:58,000 I'd be analysing the results and trying to trying to write these up and trying to write papers.

196 00:21:58,000 --> 00:22:07,000 And there is also an we have sort of a kind of lab culture say I'm part of the future of work theme.

197 00:22:07,000 --> 00:22:14,000 And every other week we would have a meeting where we would, for example, listen a presentation from one of the other researchers.

198 00:22:14,000 --> 00:22:22,000 So I think really my day could be split up with any of those tasks, depending on what stage I'm in the project.

199 00:22:22,000 --> 00:22:25,000 And I wouldn't. There is no one day that looks the same.

200 00:22:25,000 --> 00:22:33,000 And I think those types of tasks on that kind of individual level, they are very similar to what I was doing in my PhD

201 00:22:33,000 --> 00:22:43,000 And there is this other collaborative layer where you are really part of a bigger team and anybody trying to kind of help the team be successful,

202 00:22:43,000 --> 00:22:52,000 which I feel is different from from my PhD because it was kind of a very individual project and working style.

203 00:22:52,000 --> 00:23:01,000 So thinking about the emphasis on collaborative working, what experiences did you have as a research student that helped prepare you for this way

204 00:23:01,000 --> 00:23:06,000 of working or helped you develop the skill set that you would need in the workplace?

205 00:23:06,000 --> 00:23:15,000 I got involved in different types of extracurricular activities, I feel like that helped more than what was in my PhD per se

206 00:23:15,000 --> 00:23:16,000 So when I was Exeter,

207 00:23:16,000 --> 00:23:28,000 that was the opportunity to be a facilitator on Grand Challenges Week and so that was really a great point of collaboration for me in trying to

208 00:23:28,000 --> 00:23:37,000 kind of think about what what kind of team of undergraduates are doing and how I might also support them in their work and kind of facilitate them.

209 00:23:37,000 --> 00:23:44,000 So that didn't feel as kind of individual. And there were other things that I did.

210 00:23:44,000 --> 00:23:55,000 So I I'd be included on a grant application, it wasn't successful, but I kind of helped prepare some of the work for that.

211 00:23:55,000 --> 00:24:04,000 So there were kind of brainstorms and kind of workshops, sessions, and people were collaboratively authoring kind of documents.

212 00:24:04,000 --> 00:24:10,000 So that was really another aspect that really facilitated that.

213 00:24:10,000 --> 00:24:12,000 And another thing that I.

214 00:24:12,000 --> 00:24:25,000 got involved with was the widening participation programme at Exeter so that's with the with the residential team, say and also open days as well.

215 00:24:25,000 --> 00:24:30,000 So those I was working as part of a team where we collaborated said, think about what?

216 00:24:30,000 --> 00:24:35,000 What activities do you want today? Well, some of the things you want to present to people.

217 00:24:35,000 --> 00:24:40,000 So I felt like those extra curricular things were what really helped.

218 00:24:40,000 --> 00:24:46,000 And we have that kind of collaboration aspect in my PhD

219 00:24:46,000 --> 00:24:53,000 And I also mentioned the postdoc I did at Exeter. was looking at the kind of peer-to-peer energy markets.

220 00:24:53,000 --> 00:25:03,000 And that was more collaborative that because I was working in a multidisciplinary team with computer scientists and software engineers and say, yeah,

221 00:25:03,000 --> 00:25:07,000 that was a lot more collaborative in terms if we had more kind of regular meetings where we would

222 00:25:07,000 --> 00:25:12,000 give updates about the work that we've done and look at the different kind of pieces of work,

223 00:25:12,000 --> 00:25:16,000 we tried to understand how the different pieces kind of fit together.

224 00:25:16,000 --> 00:25:21,000 So I felt like it wasn't perhaps things that I did kind of directly through my PhD

225 00:25:21,000 --> 00:25:27,000 But I felt that there were other things that I got involved in during my PhD that helped.

226 00:25:27,000 --> 00:25:32,000 So what other extra curricular things you got involved with that really important

227 00:25:32,000 --> 00:25:39,000 or formative for moving onto the stock and your current job at Microsoft Research?

228 00:25:39,000 --> 00:25:42,000 Yeah. So I know that I got I took part in a summer school as well.

229 00:25:42,000 --> 00:25:53,000 So in the psychology department and social psychologists, we're part of a broader kind of the European association social psychologists.

230 00:25:53,000 --> 00:26:00,000 And there was a summer school. So I took part in that. And that was in a way of about how we have kind of grand challenges for the undergrads.

231 00:26:00,000 --> 00:26:05,000 It was sort of you kind of came in for I think it was a week or two weeks and

232 00:26:05,000 --> 00:26:09,000 we just tackled like a brand new problem or brand new area of research us

233 00:26:09,000 --> 00:26:16,000 And we kind of worked in small groups and we thought about what a study would look like and what kind of questions we'd want to ask,

234 00:26:16,000 --> 00:26:24,000 what kind of data we want to collect. So that kind of rapid and that trying to gain a rapid understanding of any topic and

235 00:26:24,000 --> 00:26:29,000 then tried to kind of spend that up into what kind of project proposal might look like.

236 00:26:29,000 --> 00:26:37,000 That was really good as well. So I think. Those types of opportunities where you know that you can be working with other people,

237 00:26:37,000 --> 00:26:43,000 doing a different type of task than you might do in your everyday work. That was good.

238 00:26:43,000 --> 00:26:51,000 And yeah, I had a few other things that I did so that I always kind of get the names of the schemes

239 00:26:51,000 --> 00:26:54,000 but I think it was I think this actually came under public outreach.

240 00:26:54,000 --> 00:27:04,000 So when I got involved in things like the Sidmouth Science Festival and put together, I just sort of like a little demo from psychology,

241 00:27:04,000 --> 00:27:08,000 but just got me talking to other audiences say those are kids, you know,

242 00:27:08,000 --> 00:27:16,000 young children and members of the public and say again, you know, I didn't even talk about my own research.

243 00:27:16,000 --> 00:27:21,000 I feel like sometimes that's a barrier or you might think, oh, I don't have anything to say about my research,

244 00:27:21,000 --> 00:27:27,000 but I just talked to them about kind of classic psychology experiments and bought them things that they could play with.

245 00:27:27,000 --> 00:27:34,000 So there's a little bit of an IQ test that they got to kind of shift ground blocks and try to put patterns together.

246 00:27:34,000 --> 00:27:35,000 But I think that as well,

247 00:27:35,000 --> 00:27:43,000 it just helped me just with communication skills and thinking about how to explain kind of research to people who aren't academics.

248 00:27:43,000 --> 00:27:50,000 So, yeah, I thought both in the communication and in just kind of planning that and setting them up and talking about the team,

249 00:27:50,000 --> 00:27:56,000 all we got to do and how are we going to do that? That was also another aspect of collaboration.

250 00:27:56,000 --> 00:28:00,000 So thinking about those those extra curricular things you did, you know, Sidmouth Science Festival,

251 00:28:00,000 --> 00:28:06,000 Granch challenges the summer school, going to a careers consultant for one to one appointment.

252 00:28:06,000 --> 00:28:13,000 What other advice would you give to current research degree students to.

253 00:28:13,000 --> 00:28:17,000 What opportunities do you think they should make the most of during their research

254 00:28:17,000 --> 00:28:22,000 degree to help them prepare for that transition to a career in research,

255 00:28:22,000 --> 00:28:31,000 but also a role outside of academia? Yes. So I think the one thing that I didn't do, which I've learnt about, is internships.

256 00:28:31,000 --> 00:28:36,000 So, you know, so organisations like Microsoft Research.

257 00:28:36,000 --> 00:28:43,000 But I think anybody anybody's interested, potentially interested in tech in the summer.

258 00:28:43,000 --> 00:28:46,000 Lots of these companies have internships where they're looking to these students.

259 00:28:46,000 --> 00:28:50,000 They're paid. They're like well paid.

260 00:28:50,000 --> 00:28:57,000 And you can go for three months over the summer, say, I think a lot of places they start to kind of advertise things in September,

261 00:28:57,000 --> 00:28:59,000 say, you know, it's a bit of forward planning involved.

262 00:28:59,000 --> 00:29:07,000 But I would definitely say to look and see if there's an internship in the type of area that you might be interested in,

263 00:29:07,000 --> 00:29:10,000 because it really does give you a head start on.

264 00:29:10,000 --> 00:29:14,000 You know, some people come back and do the internship every single year.

265 00:29:14,000 --> 00:29:17,000 So they, you know, they start in their first year.

266 00:29:17,000 --> 00:29:23,000 And then by the end of their third year, they've done an internship with the organisation three, three times.

267 00:29:23,000 --> 00:29:30,000 And you really think, you know, they've almost got kind of years work experience directly in the industry that they want to go into.

268 00:29:30,000 --> 00:29:33,000 But even if you do the internship and you might think, oh, actually,

269 00:29:33,000 --> 00:29:39,000 this isn't anything like I thought it's going to be and I've I've realised I don't want to do this.

270 00:29:39,000 --> 00:29:44,000 I think it will give you a whole new set of skills that you probably wouldn't get from your PhD

271 00:29:44,000 --> 00:29:50,000 And also, it gives you that learning. It might give you that closer understanding of what is it that I want today.

272 00:29:50,000 --> 00:29:56,000 And I think even if you kind of really feel strongly I want to go into academia

273 00:29:56,000 --> 00:30:00,000 and doing something like an internship might help you get industry connections.

274 00:30:00,000 --> 00:30:04,000 So when you're thinking about, like your own grants and how you might want to have an industry sponsor when

275 00:30:04,000 --> 00:30:09,000 they're doing internships with a relevant industry could help you get a build.

276 00:30:09,000 --> 00:30:16,000 That network can have these connections where later you can say, oh, actually, maybe I can find out these can be an industry partner on a grant.

277 00:30:16,000 --> 00:30:22,000 So I would definitely advise you to look for these things.

278 00:30:22,000 --> 00:30:31,000 I think one of the challenges that I always had thinking about my career was I had relatively limited geographic mobility.

279 00:30:31,000 --> 00:30:38,000 So I know that lots of people end up going abroad after their PhD

280 00:30:38,000 --> 00:30:44,000 And, you know, for me, because of my family circumstances, that wasn't an option.

281 00:30:44,000 --> 00:30:53,000 But I would encourage people here don't underestimate like what companies are kind of not too far off on your doorstep.

282 00:30:53,000 --> 00:31:03,000 I really I didn't even know that Microsoft had a lab in Cambridge and other companies in London isn't isn't too far from Exeter.

283 00:31:03,000 --> 00:31:10,000 So, you know, you might be surprised kind of what there os and what they're doing, the type of opportunities that they have.

284 00:31:10,000 --> 00:31:13,000 And so I'd really encourage you to think about that.

285 00:31:13,000 --> 00:31:22,000 And I'd just talk to people who I talk to people at conferences and yeah, just reach out to people on linkedin

286 00:31:22,000 --> 00:31:27,000 If you think they're really interesting and even if they're not somebody you could work directly,

287 00:31:27,000 --> 00:31:33,000 they

287 00:31:27,000 -->286 00:31:22,000 -->285 00:31:13,000 -->284 00:31:10,000 -->283 00:31:03,000 -->282 00:30:53,000 -->281 00:30:44,000 -->280 00:30:38,000 -->279 00:30:31,000 -->278 00:30:22,000 -->277 00:30:16,000 -->276 00:30:09,000 -->275 00:30:04,000 -->274 00:30:00,000 -->273 00:29:56,000 -->272 00:29:50,000 -->271 00:29:44,000 -->270 00:29:39,000 -->269 00:29:33,000 -->268 00:29:30,000 -->267 00:29:23,000 -->266 00:29:17,000 -->265 00:29:14,000 -->264 00:29:10,000 -->263 00:29:07,000 -->262 00:28:59,000 -->261 00:28:57,000 -->260 00:28:50,000 -->259 00:28:46,000 -->258 00:28:43,000 -->257 00:28:36,000 -->256 00:28:31,000 -->255 00:28:22,000 -->254 00:28:17,000 -->253 00:28:13,000 -->252 00:28:06,000 -->251 00:28:00,000 -->250 00:27:56,000 -->249 00:27:50,000 -->248 00:27:43,000 -->247 00:27:35,000 -->246 00:27:34,000 -->245 00:27:27,000 -->244 00:27:21,000 -->243 00:27:16,000 -->242 00:27:08,000 -->241 00:27:04,000 -->240 00:26:54,000 -->239 00:26:51,000 -->238 00:26:43,000 -->237 00:26:37,000 -->236 00:26:29,000 -->235 00:26:24,000 -->234 00:26:16,000 -->233 00:26:09,000 -->232 00:26:05,000 -->231 00:26:00,000 -->230 00:25:53,000 -->229 00:25:42,000 -->228 00:25:39,000 -->227 00:25:32,000 -->226 00:25:27,000 -->225 00:25:21,000 -->224 00:25:16,000 -->223 00:25:12,000 -->222 00:25:07,000 -->221 00:25:03,000 -->220 00:24:53,000 -->219 00:24:46,000 -->218 00:24:40,000 -->217 00:24:35,000 -->216 00:24:30,000 -->215 00:24:25,000 -->214 00:24:12,000 -->213 00:24:10,000 -->212 00:24:04,000 -->211 00:23:55,000 -->210 00:23:44,000 -->209 00:23:37,000 -->208 00:23:28,000 -->207 00:23:16,000 -->206 00:23:15,000 -->205 00:23:06,000 -->204 00:23:01,000 -->203 00:22:52,000 -->202 00:22:43,000 -->201 00:22:33,000 -->200 00:22:25,000 -->199 00:22:22,000 -->198 00:22:14,000 -->197 00:22:07,000 -->196 00:21:58,000 -->195 00:21:52,000 -->194 00:21:44,000 -->193 00:21:37,000 -->192 00:21:32,000 -->191 00:21:27,000 -->190 00:21:19,000 -->189 00:21:14,000 -->188 00:21:06,000 -->187 00:21:01,000 -->186 00:20:50,000 -->185 00:20:42,000 -->184 00:20:36,000 -->183 00:20:29,000 -->182 00:20:22,000 -->181 00:20:15,000 -->180 00:20:09,000 -->179 00:20:01,000 -->178 00:19:55,000 -->177 00:19:49,000 -->176 00:19:41,000 -->175 00:19:34,000 -->174 00:19:27,000 -->173 00:19:19,000 -->172 00:19:12,000 -->171 00:19:04,000 -->170 00:19:01,000 -->169 00:18:52,000 -->168 00:18:49,000 -->167 00:18:43,000 -->166 00:18:34,000 -->165 00:18:26,000 -->164 00:18:16,000 -->163 00:18:07,000 -->162 00:18:02,000 -->161 00:17:55,000 -->160 00:17:49,000 -->159 00:17:45,000 -->158 00:17:41,000 -->157 00:17:34,000 -->156 00:17:30,000 -->155 00:17:23,000 -->154 00:17:22,000 -->153 00:17:14,000 -->152 00:17:06,000 -->151 00:16:58,000 -->150 00:16:49,000 -->149 00:16:43,000 -->148 00:16:35,000 -->147 00:16:30,000 -->146 00:16:26,000 -->145 00:16:18,000 -->144 00:16:15,000 -->143 00:16:10,000 -->142 00:16:02,000 -->141 00:15:56,000 -->140 00:15:51,000 -->139 00:15:44,000 -->138 00:15:34,000 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00:10:01,000 -->86 00:09:54,000 -->85 00:09:46,000 -->84 00:09:43,000 -->83 00:09:36,000 -->82 00:09:30,000 -->81 00:09:23,000 -->80 00:09:18,000 -->79 00:09:13,000 -->78 00:09:00,000 -->77 00:08:51,000 -->76 00:08:44,000 -->75 00:08:36,000 -->74 00:08:27,000 -->73 00:08:21,000 -->72 00:08:14,000 -->71 00:08:05,000 -->70 00:07:58,000 -->69 00:07:48,000 -->68 00:07:43,000 -->67 00:07:37,000 -->66 00:07:29,000 -->65 00:07:23,000 -->64 00:07:13,000 -->63 00:07:09,000 -->62 00:07:04,000 -->61 00:07:00,000 -->60 00:06:48,000 -->59 00:06:42,000 -->58 00:06:31,000 -->57 00:06:25,000 -->56 00:06:18,000 -->55 00:06:05,000 -->54 00:06:01,000 -->53 00:05:55,000 -->52 00:05:49,000 -->51 00:05:48,000 -->50 00:05:39,000 -->49 00:05:32,000 -->48 00:05:22,000 -->47 00:05:14,000 -->46 00:05:07,000 -->45 00:05:00,000 -->44 00:04:54,000 -->43 00:04:50,000 -->42 00:04:44,000 -->41 00:04:35,000 -->40 00:04:28,000 -->39 00:04:19,000 -->38 00:04:12,000 -->37 00:04:08,000 -->36 00:04:04,000 -->35 00:03:56,000 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