Stories from Beyond Academia #19: Melanie Zeppel
(PhD in Plant Physiology)
Moving cities (or countries!) is not at all uncommon within an academic career. In fact, we recall various conversations when we were doing our PhDs in which it was suggested that such a move was a ‘non-negotiable’ for success in academia. But if this is an expectation for success in academia, then what happens if you’re not super keen on the idea?
This is one of the reasons we’ve heard for PhDs considering a non-academic career. And, we think, fair enough too!
In this story from beyond academia, we talked to Dr Melanie Zeppel about the role this particularly disruptive factor had to play in her decision to move out of academia, and what ‘redefining success’ has looked like for her.
Melanie has a PhD in Plant Physiology, is a Superstar of STEM, and had many grant successes (including two fellowships and two ARC Grants funded!) as well as an offer of a permanent faculty position (albeit on the other side of the country) before she decided to make the switch into the world of carbon data science.
And does this mean she wasn’t committed enough to science? We say no way: she just managed to figure out how to conduct science outside academia, and work in the field in which she is a subject matter expert (her role now is at New Forests in Natural Capital and Carbon Analytics) in a way that allows for growth and career progression, and works for her.
JM: Melanie, welcome and thanks for your time! Let’s kick things off back at the beginning of your career story – could you tell us a bit about what you were doing for your PhD, what you were researching and what did you find?
MZ: Thanks for having me! My initial research question was how the water use of trees compares between a remnant forest (uncleared vegetation), versus a plantation and a pasture. And somewhat amusingly, although painfully at the time, I started my PhD during the millennial drought, so the trees weren't using very much water at all. I learned a valuable lesson about pivoting, though, and I re-focused my PhD on how much water trees use during drought, which meant that I segued into doing tree physiological research on climate change and elevated CO2 drought rising temperatures.
We found that if you compare bodies in a remnant forest and a plantation, they use similar amounts of water. But the eucalyptus did something which we didn't know before: when there was a drought, they did not drop their leaves, they hung on to their leaves and had these raggedy, shredded, grimy, really, really old leaves but the transfer of oxygen and water was quite low – we had a piece of equipment called a porometer, and we measured stomatal conductance which is the exchange of gases. After it rained, the trees dropped those leaves and grew fresh new leaves, and those fresh new leaves had really high levels of transpiration.
JM: You're seeing a mechanism that’s essentially the tree doing everything it can to conserve water when water is not available, and then when water becomes available all those leaves are quickly sacrificed?
MZ: Yes, and actually Australian trees, southern hemisphere trees, behave quite differently to northern hemisphere trees. So just like how a lot of experiments are done in mice and then results are extrapolated to humans which is quite wrong, a lot of the research on vegetation and forests and plant responses to climate change comes out of North America and Europe, and northern hemisphere forests are largely deciduous and behave in particular ways that you just don’t see in the southern hemisphere. It doesn't happen in Australia, doesn't happen in South Africa.
So one of the other interesting things that I observed during my research, and also kept pushing for, is people would do an experiment on trees in say New Mexico and they'd say, “Oh, this is how trees behave”. And we would say “no, no, New Mexico is one state, in the Northern Hemisphere, and you can't say that all trees do this”. We kept pushing that Australian vegetation is adapted to fire and drought and low nutrients and the vegetation just respond in incredibly different ways. There was a lot of advocating to get more southern hemisphere vegetation in the literature generally.
JM: I actually heard of ‘tree blindness’ recently, where people without training would look at a group of different trees and consider them all to be relatively homogenous, whereas once you’ve learned more about the different species of trees, you’d look at that same group of trees and note that the group contains maybe sixteen different species and that they react differently to all sorts of environmental stressors, and so on. And I’m reminded of this in hearing about your research and some of the challenges you encountered: you can't just go “well, we've got these New Mexico trees doing this thing so therefore all trees must do that thing”. It'd be like saying this one mammal from New Mexico does a particular thing so therefore all mammals must do it.
MZ: Yes, I’ve seen exactly this when working with some colleagues who were modeling vegetation, and we were walking around Santa Barbara and we spent two days discussing how you could model how trees die, which is quite complicated. But then we went on a hike around the California forests, and someone asked about the species of one particular tree, and the modellers said it was a conifer almost as though that was all we could possibly need to know. But the people who actually had the expertise in working with conifers were asking what kind of conifer, what species, what genus. So yes, absolutely, tree blindness.
JM: You stayed in academia for a while after you did your PhD. Were you continuing to work on tree responses to drought? In that sort of area?
MZ: I've actually written a “Tenure, she wrote” post about my thoughts on leaving academia, and the whole post is actually around redefining success. I spent a long time trying to have the most sparkly and robust and strong CV because what I wanted was to keep working in Sydney. And I spent a lot of my focus on trying to have a really strong CV with lots of publications and grants to maximise my chances of that.
I got a Macquarie University Research Fellowship, one of only six they awarded and they’d had over 200 people apply. I had the privilege of working with Belinda Medlyn, who's an amazing professor who taught me so much about stats. And then after that, I won a DECRA which was also amazing. So for six years, I had functionally no supervisor, I had research money, I could choose who to work with and to try and answer the most pressing questions. I was broadly researching how trees respond to changing rainfall, and this was 10 or so years ago. Under climate change we know that the weather will become more extreme, rainfall will become more extreme with more droughts, more floods. And I was conducting experiments on how plants will respond to that.
I did a really interesting synthesis, a literature review, of global literature on if you take the rainfall from autumn and move it into spring but you've got the same volume then how do plants respond and also we did some glasshouse experiments on if you keep the volume of precipitation the same but you just shift when it occurs.
JM: You mentioned learning a lot about stats and that foreshadows where you went next. I comfortably admit you had a lot more success in academia than I did, but when we moved from academia we both went into that analytics and data science space. What was it for you that prompted that move and to decide that was the direction you wanted to go in?
MZ: At the conclusion of my DECRA, I thought I probably should be getting a permanent job because I was at the stage in life where I had a mortgage and children and didn’t want to keep moving cities. And I actually was offered a permanent faculty position at one of the universities in Western Australia. And I was going for a run with one of my running friends and he just said, “I would never move cities for a job” and I realised I didn’t want to move cities at all. And why should I change cities? I have grandparents close by here who help me with my kids. The father of my kids is here. I have a whole lot of support structures. So instead of taking that job and changing cities, I just ended up changing careers. And I went from tree physiology to genomic medicine. I didn't want to move cities and I met someone at a seminar and she talked about her centre and I sent her my CV and it was quite strong and I was offered a job. I think a message from all of this is that you can have an incredibly strong CV and still not land a permanent job in academia, and you can have an incredibly strong CV and still just go “No thanks. It's not for me”.
…you can have an incredibly strong CV and still not land a permanent job in academia, and you can have an incredibly strong CV and still just go “No thanks. It's not for me”
It was around 2019-2020 that I moved out of the University sector. I was walking around the campus and I saw someone I knew and I said, “Oh, really great to see you, do you want to collaborate on something?” The last time I spoke with them they had PACE students, which was a University program where you’d pair a student with an industry partner, so the student gets industry experience. And I met that person and I said “'I've got some great projects. Do you have any students?” And the person told me they didn’t have students, or a job anymore as they’d been made redundant. And then I met someone else, I’d worked with them years ago, and they told me they'd been made redundant too. At that point, there were five faculties, and the University removed an entire faculty and merged the five into four, and there was just this whole atmosphere of cost cutting.
I’d been in academia by that point for 16 years. When I started, it was all about exploration and discovery. You would come up with a hypothesis and do some literature review and do some experiments. And there were people who would process your receipts and people who would help with your travel, and it was already death by 1000 cuts. Then 16 years later, the amount of funding that people were getting was less and less and less, the amount of admin for travel or managing grant budgets, instead of having someone help you, they would just give you a spreadsheet and say you have to work it out. Figure out which little cell corresponds with how much money you've got left.
Basically, I just thought universities had changed, and it wasn't satisfying. And I was at a Level C and I’d reached the top of that level. The next level for me would have been largely administrative, whereas I love research, I love experiments, I love learning. The people above me were Heads of Departments, or in charge of managing academic workloads of entire faculties and that didn’t look particularly fun. Also, I looked at the percentage of women who were professors and I thought that doesn't inspire me.
Beautifully, I was having dinner regularly with a group of five to eight friends who had gone to Macquarie Uni and two of them by that point had moved out of academia. And we would catch up and have drinks and one of them told me how they finish at five o'clock and go for a run. Like wow. As an academic, I'd be working Friday nights and working through the weekends whereas she’s telling me she didn't even check her email on the weekend. I honestly wondered why I was staying in academia.
There was a whole lot of soul searching. I had to work out for myself what success was because I had been surrounded by people who were saying that success is when you stay in academia. If you ‘leave’ then you haven't ‘made it’. But for me, I thought success is having a job that I enjoy and having a job that's fun. Success is having a job where my children can see their grandparents rather than living in a totally different city. And honestly, a job where there are people in positions senior to me and I can think I’d want to progress to that. Especially women who are mothers who hold senior leadership roles. So that is what prompted me to move.
JM: All very compelling reasons! And what was it about the analytics and data science route that inspired you?
MZ: I think I saw an article that proclaimed data science to be the sexiest career of 2017 or something like that which made me wonder ‘what is data science?, so that prompted me to do one of those online courses that's like an hour long and the course was basically covering how data science basically involves reading in some data, cleaning it, analysing it and running some stats using R or Python, and then answering a question. And, I mean, that sounds like what I did during my PhD and my postdocs.
Everyone who has done a PhD, I think, if they wanted to, could work in analytics or in data science. I love data and I really felt that was something that I could do. After that, I did a whole bunch of courses on Coursera and on LinkedIn, data science for Python, or data science for R, or machine learning for Python until I felt like I could call myself a data scientist. Overall I did a whole lot of online courses in the evenings and I think they're really, really helped.
JM: We did some very similar things: online courses in R were a big part of my preparation to move out of academia too, so there you go – two people who have successfully moved from different kinds of PhDs into jobs in a similar field both saying go do some online courses in R! Now, since you moved out of academia, you’ve been very successful, you’ve been recognised through several awards. Can you tell us a bit about what you've been doing since you moved out of academia and a bit about those achievements?
MZ: Honestly, I think one of the keys to successfully moving out of academia is having a really strong network. It was some of my amazing, supportive peers and mentors that told me about some of these award opportunities and prizes and encouraged me to apply. For example, the Women in AI in Agribusiness prize. I felt that I was not ready or qualified enough to go for that prize, but I had been communicating with this woman on social media and she got in touch out of the blue to encourage me to apply for that award, and that support was really, really helpful.
I also joined Franklin Women and they run these amazing events for supporting careers, and one of their events was writing Wikipedia pages for women in STEM. In one of those events, I wrote a Wikipedia page for someone called Sue Barrel – she’s stellar, she goes around Australia talking about women in STEM. I emailed her and gave her the process to follow if she might want to upload a photograph of herself and she was lovely and generous: we exchanged phone numbers and I asked her advice about when I was making the move, and she recommended that I apply for one of these prizes too.
The first job that I took when I moved out of academia was not my first choice if I’m honest. I took a role at Westpac, I was working as a statistical analyst.
JM: Wow, a lot of similarities – I worked at Westpac too.
MZ: Yes, and good on Westpac for being open-minded and taking people who have been in academia. I applaud them for that. It was a really supportive workplace and I learned really useful things. When you're working in a university, you're surrounded by people who have PhDs and people who self-select for that environment. They like working hard, they're probably intelligent, and if they come across a problem they are proactive and don’t give up until they solve it. They know how to write a good paragraph, how to organise some numbers. A lot of people outside of academia don’t really know how to organise a dataset, or handle data confidently. There are lovely, brilliant people outside academia, but I think you don't realise until you leave academia just how much you’ve learned in a PhD and how those skills can transfer, skills like resilience, perseverance, writing that paragraph.
There are lovely, brilliant people outside academia, but I think you don't realise until you leave academia just how much you’ve learned in a PhD and how those skills can transfer, skills like resilience, perseverance, writing that paragraph.
JM: And those things are so normalised when you're surrounded by people who are operating at that level, that’s just normal operating in that context and sometimes you may find you go into another context and realise that a PhD cohort is a very select group of people.
MZ: I felt like I could do my work in about four hours a day at Westpac, and so did a lot of people in my cohort, because we're so used to being so time efficient, cramming work into our days. So that role at Westpac was great for me. I learned if you're going to communicate some information to someone, they're going to trust that you've cleaned the data and that you've done all that background work because they just want your opinion in five seconds. They do not want the background, they don't want the methods, they don't want the caveats, they don't want 15 references.
It's really refreshing in a way, I love not having to deal with reviewer two, I love that someone asks if I can answer this question, they give me the data, I pretty much give them the answer in a PowerPoint slide, and I just get to move on to the next thing. I don't have to send it to co-authors. I don't have to reformat the font for the different journals I’m submitting to. I don't have to apply for my salary. I don't have to spend months and months and months on grants. It's so amazing.
JM: And how did you find that first Westpac job, was that a job ad that you saw and you then submitted an application?
MZ: I changed my LinkedIn settings to ‘open to recruiters’ and a recruiter reached out and messaged me and that’s how I got the job. Also, having a really strong network was important. One of my ex-Macquarie Uni friends was also working at Westpac at the time and we were talking and they said to me “oh, you're having an interview with Westpac – well, just FYI, they're having a hiring freeze next week”. I told the recruiter, and he was like “okay, let's expedite this” and we just got everything done on the Friday afternoon. He came back to me and told me if I could arrange for my referees to submit their reports by Monday 4pm, then I’d have a job offer.
I had all these professors as my referees but of course they were doing important things so I needed to come up with other referees who had worked with me and would be willing to shift what they’re working on to fill in this referee report for me urgently. They had to fill in an online form saying how long they've known me, what my skills are like, etc, etc. So having three people who were willing to drop everything and turn this report around for me within something like two hours. That network really helps.
JM: I think that’s indicative of the pace at which things happen in private sometimes. For me, I agreed to have a coffee with the guy who knew someone I knew, at the end of this 20-minute coffee he offered me a job! I was not ready for that. It was just the polar opposite of spending months and months writing grant applications.
MZ: I'm part of the Superstars of STEM program, which Science Technology Australia runs, and some of the others in that program have said they’ve been applying for DECRAs and Future Fellowships and the deadline for announcing results in those schemes has just been pushed back for six months. So that has really quite significant impacts. I might have my facts wrong, but the comments were very much along the lines of ‘this is not good’. Like what if you've got funding that goes to a particular month and that’s before the announcement is made, who is going to cover you for that extended period of time? Is the lab going to have to come up with six months of extra salary, or are you going to have to go without salary while you’re waiting to hear?
I really love that’s not something I need to worry about. I turn up for work, I do what I’m asked, I'm still doing science, I'm still doing data analysis, I'm still working with forests and trees. I really, really love the organisation that I work for now. And I don't have to write a grant.
JM: We talked a bit about how you snagged the first role out of academia, but before that I think you were just about to talk about the second role you went into?
MZ: Yes, after a year or so I got headhunted to work in a role that was more similar to my academic background. I think that likely happens to a lot of people. I was working for a company that measured soil carbon using machine learning, which was really cool. And now I work for New Forests, which is an asset management company, with $11.7 billion of assets under management, who manage 1.3 million ha of sustainable timber forests and conservation areas, as well as carbon and conservation finance projects, agriculture and timber processing. The forests and agricultural assets are in Australia, New Zealand, Asia, Africa and the USA. New Forests has investors in Europe, the UK, Australia, Asia Pacific, and North America, including pension funds, sovereign wealth funds and superannuation funds. Investors want to make sure the funds are invested in assets which are provide the opportunity for a strong investment return, are sustainable, have social and environmental impact, and the forests are being managed responsibly.
I run the data analytics for the carbon, so quantifying how much carbon dioxide is removed from the atmosphere. Many investors want to know that their superannuation funds are having an impact. We also do things like measure how many women are on boards, how many women are employed, how many rare and threatened species are in the forest, and net zero emissions. For that I'm working with the assets that we own like the forestry assets, and helping them set their net zero targets.
New Forests is an industry leader in measuring the scope three emissions because scope three emissions are really complex, they're really outside your boundary of control, but we're forecasting them and there's a lot of modeling and a lot of data and a lot of assumptions. But I feel like I'm really helping Australia move towards its net zero goals and helping this organisation set targets for reducing emissions, which is pretty satisfying.
JM: It sounds fascinating, is that under the umbrella of social impact investing? Am I getting my terminology right?
MZ: Yes, and I'm still working on science, I'm doing data analysis. It's wonderful. The people are lovely. I've got a really supportive boss, who is very encouraging. And actually one thing I noticed about going from academia to industry, in academia you've pretty much got like seven jobs: review papers, review grants, write your own papers, write your own grants, be on committees, contribute to policy. And then when I went to industry, both at Westpac and working in my current role with my current boss, they will guard my time, they say they want to make sure that I’m not working too hard, not working in the evenings. And I’d never heard that before. They’re trying to ensure their staff aren’t burned out.
It’s remarkable compared to in academia where you manage your own time and you're encouraged to be a ‘super achiever’, where the metrics are the more publications and the more grants you have, the more promotions you'll get. Whereas now, I have supervisors who are amazing. They provide positive feedback. They guard my time. They ask to hear about any blockers I have and looks to try and remove those blockers.
JM: I'm just thinking about what you said about academia, and there's always someone who's willing to work that one hour more than you on a Saturday. So it’s great to hear your boss is saying ‘wait a second, let's put some guardrails around this’.
MZ: There are times when I want to work longer hours because I want to deliver. But I also know that if I’ve been working 12- or 14-hour days recently, then supervisors will say, ‘Okay, let's shuffle things around. Let's speak to someone to make sure you're working sustainably on sustainability’ which is great.
JM: I guess in the content area you're working in, there must be some really obvious similarities between the skills and experiences from your PhD and what you're doing now – I assume, knowledge about the plant science side of things, the data analysis side of things, presentation, report writing would all carry over. I'm wondering if there are other skills or experiences from your academic days that you think have carried over that were maybe a bit less obvious or maybe surprised you a bit?
MZ: I think you don't realise until you leave academia, but when you complete a PhD you encounter problems and you learn you are capable of solving them. For example, there was one time when I was driving a four wheel drive out to a remote forest and I accidentally put unleaded into the diesel fuel tank. I remember back to that time, I was standing at the petrol station, I had a bit of a cry, I rang a bunch of people, I asked different people for their solutions, but I just came up with a solution.
And so I think resilience is a key skill you learn. When you do a PhD, most people they do bleed, they do cry, and they do sweat, particularly if the PhD involves working in forests. I don't know about psychology, if there's blood involved, but I assume there’s tears and sweat, and so resilience. Most people who have got a PhD have learned grit and resilience.
Also the ability to analyse data, basic statistics, even the most basic statistics is useful in industry. Being able to write a paragraph or a report that reads well, is coherent and well-referenced, that’s a really useful skill and very transferable. Also being able to communicate complicated messages simply, and using PowerPoint, how to give a presentation. I think most people who have finished a PhD will just have so many skills that they won't be aware of that are transferable.
JM: Sometimes the skills feel pretty basic but that can be all that’s needed. You might put a confidence interval around a point estimate in industry or in government or whatever and people respond like ‘what is this witchcraft?’. And you realise that’s a good contribution to your day’s work, putting a line around a dot to indicate that level of uncertainty. So that was a beautiful way of articulating the value that you could bring across.
And that, I think, is a nice segue into my last question for you, which is if you have any particular advice that you'd give to someone who's maybe a late-stage PhD candidate, or they're in that postdoc cycle or grant cycle and want to look elsewhere?
MZ: First off, I’d advise that they really work on their networks because a lot of the time you will hear about a role through your networks, and your networks can help you with references at the drop of a hat if you need them. I'm definitely on LinkedIn, and I would advise changing settings to be ‘open to recruiters’: that's how I got my first job out of academia. It used to be that if you were active on Twitter, that would be helpful, but I think that's now in the past. Now, being active on LinkedIn is helpful for developing a profile and also putting keywords on your profile. I put things like carbon, machine learning.
I would definitely say make sure that you have got some R or Python skills if you’re interested in analytics. If you don't want to be in data science, you could be a data engineer or data analyst. But I put off learning for a long time because I remember thinking I was better at winning grants than I am at learning to code so I’d just buy an SPSS licence. But that was, in hindsight, a bad idea. If I'd learned Python much earlier, it would have been so helpful.
I also suggest learning how to write a two-page CV for industry. You get so much advice on publications and ‘publish or perish’ but nobody in industry cares how many publications you have or what journal they're in or what impact factor. I sent my CV to some people who already had been in industry and then they sent me theirs and then I crafted mine to be a bit more to be industry relevant.
I also had some advice to practice a job interview, video yourself on your laptop, and answer typical questions that you're bound to get like, ‘tell us about your career’, ‘why do you want this job’, ‘what do you bring to this job’, ‘what are your strengths’. Practicing those kinds of questions would be really handy.
One more thing regarding cover letters, you’ll need a cover letter for industry job applications and there are some standard paragraphs you might want to include in pretty much all the cover letters you will write. One paragraph might be on evidence you can work in a team, evidence you can analyse data, evidence you have experience with x, y ,z. When you're applying for a job, you’ll need to respond to the selection criteria otherwise you just won't make it through. So having those paragraphs written has been helpful, making it much less daunting. I could find a job I was interested in and know I've already got those paragraphs written and ready to go.
Also, that first job, you might not love it. I've heard a lot of people in industry say they don't want to hire academics, no one will ever tell you that if you're in academia but I did apply for a number of jobs, and just like writing a paper I just applied for another job, I submitted another cover letter, I didn't take it personally because the job market fluctuates. And finally my brother said, “I think you are going to be twice as happy and earn twice as much”. And I think he's right. I think I am twice as happy, I have a great boss who supports me. I don't know if I'm earning twice as much but it's more. So honestly, embrace it, don't be scared, reach out.
JM: Thank you so much, and some great advice in there as well. And just to reiterate what you say about cover letters, I do a fair bit of recruiting these days and my take on that is ‘don’t make me infer something’ because when I’m hiring I’m reading so many applications and I’m tired! So I agree on having standard paragraphs that address the criteria and making it really obvious to the person who's reading it how your paragraph addresses the criteria.
MZ: Even if the first essential criteria is ‘must be able to work in a team’ or ‘must be willing to work with occupational health and safety’. And if the start of the first sentence in your paragraph is ‘the evidence that I can work in a team is…’ or ‘my willingness to work with occupational health and safety is…’. I'm pretty sure the people on the recruitment panel just tick.
JM: Yes, from my perspective we are not looking for beautiful prose, we are looking for information that is easily accessible.
MZ: For sure, if the job ad references whether you have the right to work in Australia then address that directly saying something like ‘I am an Australian resident and have working rights in Australia’. Just don’t make them guess. Just make it all as easy as possible for the panel to decide to interview you.
And with that, we thank Melanie for sharing her career story and her insights. It was really interesting to see quite a few parallels between Melanie’s career and both of our careers - and uncanny parallels with one of us, in particular!
Side note: neither of us have felt like we’d need to completely uproot our lives every few years to have successful non-academic careers - and if a move was on the cards, it would be just as likely to be motivated by lifestyle considerations!
If you are a PhD who has moved beyond academia and you are interested in sharing your story, please get in touch with us via our LinkedIn pages - Sequitur Consulting, Sam, Jonathan - we’d love to hear from you.
Interviews have been edited for length and clarity. Views, thoughts, and opinions expressed by persons interviewed in this series are solely that of the persons interviewed and do not reflect the views, opinions, or position of Sam, Jonathan or Sequitur Consulting.