In the first of a series of dialogues with Early Career Researchers about funding models, our CEO Maya Gavin speaks with Postdoctoral Researcher and 2023 Schmidt Science Fellow Coco Newton about interdisciplinarity, what's wrong with our current grant models, and how to design more flexible funding models.
A Dialogue between Coco Newton (CN) Maya Gavin (MG).
MG: I’ll start by asking you what you’re currently working on, both in terms of your research and your more entrepreneurial projects?
CN: I'm a Postdoctoral Research Fellow with affiliations at three universities. My background is in cognitive neuroscience, and I’m now working in systems design and engineering. One of my projects involves interviewing stakeholders in the dementia diagnosis pathway to design a new wearable device for healthier brain ageing. Additionally, I work on projects funded by the Dementia Research Institute and the National Institute for Health focusing on early spatial navigation and cognitive changes in people at risk of Alzheimer’s, alongside biomarker analysis and neural imaging to better understand what type of biological underpinnings there are behind behavioural changes with Alzheimer’s.
MG: A truly interdisciplinary trajectory. Why did you choose to pursue an academic pathway, given that it’s not the most appealing for many PhD students today?
CN: Initially, I wanted to be an architect, but I ended up pursuing biomedical science as an undergraduate. For many years, I hesitated whether to switch to architecture, but my growing interest in neuroscience, particularly in how the brain perceives environments, led me to the field of navigation.
During my undergraduate, I worked in a lab at UCL and loved the academic culture. This is what motivated me to pursue a PhD. I wanted to study the link between navigation and Alzheimer's disease.
Later on when I began my PhD, I organised a conference on medical technology innovation through the Building Bridges in Medical Sciences society. There, I met Tony Kouzarides, a serial founder and academic spinout leader. He upped my mindset to consider that I could do that kind of science. This led me to entrepreneurship programs, and I realised I really enjoyed combining research with entrepreneurial ventures.
As I grew older, I understood my strengths better and felt they were wasted in a purely research role. I wanted to stay in academia but also engage in spinouts and policy advisory roles. So now, I envision myself rising in academia while exploring opportunities in industry or venture capital, always driven by a combination of curiosity and impact.
MG: It’s refreshing to see your generalist attitude paired with strong technical expertise - shifting between neuroscience, design and entrepreneurialism. Interdisciplinarity is a buzzword in academia today. What does it mean to you, and what is its core value in science?
CN: I think interdisciplinarity is the fundamental reason why breakthroughs in science happen, because it sometimes takes outsiders looking in to start asking the right questions, and then the people from within are able to answer them.
Being funded by the Schmidt Foundation has made me appreciate interdisciplinarity so much more, as it is one of their pillars. Meeting other Schmidt fellows from different areas and hearing lectures from senior academics and CEOs; what’s common between all of them is an interdisciplinarity.
For me, interdisciplinarity means being an expert in one thing but having an interest in something else, and finding other experts you have chemistry with to start asking interesting questions. True interdisciplinarity involves bringing baggage from your old discipline into a new one, creating cognitive frameworks that can lead to new insights. It can happen between several people, but it can also happen within a person.
Regarding the environments needed to foster interdisciplinarity, people need to develop expertise in a single field first, so they can then meet others with the same level of expertise in a different field. I think that studying a degree labeled as ‘interdisciplinary’ isn’t effective without sufficient depth of knowledge; it spreads you too thin. You've got to create enough water cooler moments for these encounters to happen. It’s a quality that you can’t force.
MG: I hadn’t previously thought of interdisciplinarity as an event; as the moment when certain minds or ideas meet at a particular point in time. Universities have such rich resources when it comes to the potential for interdisciplinary events, but apart from sitting at dinner with people from different disciplines, it’s quite difficult to pick each other's brains and forge unlikely methodological links.
Something that came to my mind as you were speaking is the concept of emergence. I first came across the concept in my biology classes at school whilst studying the cell; the basic unit of life. When different organelles come together within the context of the cell, what you have is the emergence of more than just the sum of the parts; you have something new - life - arising.
We need to seriously consider this when aiming to produce interdisciplinary or innovative events. How can we create environments where the resources—‘cell parts’ if you will—of the university generate new emergences? Encouraging fellowships where scientists ‘swap’ places or creating focused research spaces with resources to foster different technical developments could help. Funders, I think, have a significant role in enabling researchers to move and pivot.
It’s funny, I hadn’t expected discussing the concept interdisciplinarity. But I do want to pick your brains about about research funding models and their effects on the quality of science. What do you think are the core issues at stake when it comes to the way research is funded today, especially when it comes to Early Career Researchers (ECRs)?
CN: I can only speak from my own perspective. And I would say that I feel quite unusual among postdocs in that I am ready to take on a role as a Principal Investigator and start writing grants for my own research program.
My main frustration is that I'm not eligible for many grants because I'm not affiliated with a university at that level. Being on a fixed-term contract, I can't apply for grants that usually require a professor with a track record of holding multimillion-dollar grants.
Aside from the big project grants, another frustration is attaining small grants. The timeframe from writing to submitting, then waiting through the rounds until funding is available (sometimes a year), slows the science down. Especially in competitive areas, where several groups may be working on the same project, you can't afford to wait a year and a half to start showing evidence of output.
You have ideas you want to enact, but when you apply for funding, it's often for projects you've already started. Then you have new projects for the next grant cycle, so you're constantly gaming the system. The speed of funding and availability of small grants restricts scientists from doing what they want to do.
Many postdocs I have spoken to agree that as a result, a lot of grant applications aren't truthful. I’d be interested to know how many grants are spent as initially proposed. I don't think that number would be very high.
MG: I agree, temporality is key. Academics now commonly joke about returning to the patronage system. Putting the jokes aside, no-strings-attached funding is crucial instigator for outlier ideas that drive scientific discovery.
There has been talk about encouraging more experimental or high-risk research. But as Michael Nielsen has spoken about, many ‘high-risk’ funding programs have success rates of around 80%, raising the question of how high-risk they actually are. Perhaps high-risk funding should aim for a 50% failure rate to be genuinely experimental.
Some funders, like the Villum Foundation and Volkswagen Foundation, have tried for ‘unorthodox’ ideas that might not be submitted otherwise. They received interesting ideas, with 50% of applicants saying they wouldn't have submitted their ideas without anonymity.
I want to ask you, what are some genuine methods to address these issues in funding and to regenerate risk in scientific research?
CN: A win-win solution for both academics and funders would be the availability of more pilot funding. For example, 5 or 10k would allow academics to run initial experiments to test the feasibility of a project. While not always possible in all sciences, it's feasible in most disciplines. This can be published as a pre-registered study showing the planned work and pilot data.
From the funder's perspective, small amounts of funding don't require deep assessment, and they get the prestige of spotting promising projects early, similar to a startup seed funding model. This approach also de-risks the process for funders.
I think this would lead to better quality science overall. The general tendency is to start a project without a stage-gate method for stopping and evaluating progress. With small pilot studies, researchers could stop and analyse the data, reassess methods, and decide if the project should scale up. This forced point to review would make the larger-scale version of the science more efficient and likely to succeed.
The tenure track model is also foundational: giving new academics a start-up grant of e.g. 25k or more with no strings attached, reviewed after two years against specific criteria. Half of the problem in academia is having the job security, time and space to actually think about what you want to do. This would give academics that creative space, rather than rushing ideas for the next grant deadline and waiting a year for results.
MG: How have you navigated the ability to pivot in your academic projects?
CN: At the end of my PhD, I realised I wanted to pursue implementing innovation in dementia diagnosis, but it wasn't possible within my field. I couldn't sidestep into new fields with my previous funder. Implementing the science I helped validate clashed with my career path, and staying in my field wasn't an option. Forming a company to spin out the science was the only alternative.
If not for my current funder, I wouldn't have considered switching fields. Reading their application call made me realise that I needed to pivot to find the right tools and methods for my research. I think this is such a cool way of doing science: being guided by the tools and methods you need to answer a particular question, or implement a particular solution, rather than being constrained by the available ones in your discipline. While as a researcher you would usually pivot to learn about new subjects, what led me to pivot was searching for new ways to implement and design systems. I was aiming for science translation, which I hope becomes more common.
Implementation in science is, I think, one of the main challenges in academia today. It's about giving scientists tools to create real-world impact without pushing their science onto the public. It's entrepreneurial at its basis: understanding problems, and reverse-engineering solutions. I wish there was a mechanism for more scientists to be trained like that, and to be funded to do that. I've talked to so many scientists who say to me, “Oh, it's so cool that you're able to work out how to implement your science, and you're in design engineering. I wish I could do that”.
Inherently, us scientists are really the only people in the world who are going to be able to successfully implement what we're doing because we understand it, and we understand how to tailor the science. But we need to learn from end users and have intermediaries like industrial designers or engineers to guide the process. This is a major bottleneck that needs solving to get more science out of the lab.
MG: Is the idea of ‘impact’ as we know it still the best concept for this process?
CN: I agree that ‘impact’ has become hard to define. But I don't know how else to describe the phenomenon it's trying to encapsulate: using science to bring about a change that makes the world better.
The challenge is defining 'better.' Is it from a user perspective or an economic perspective? Especially in healthcare, I constantly grapple with what metrics to use for success. Is it cheaper delivery of the same service, better quality of life for patients, or more sustainable use of materials? Or is it a combination of all three?
Everyone should be guided by impact. There is, of course, space for blue sky research because it can generate new ideas leading to even greater impact. But fundamentally, science should be driven by questions of how it will make a difference for people.
