Learning how to coding brings career benefits and helps science by aiding reproducibility, Julie Gould discovers.
Jessica Hedge tells Julie Gould about how she learned to code as a PhD student, and the freedom and flexibility it provides to manage large datasets.
“I never saw myself as a coder and it took me a long time to realise I had to pick up the skills myself,” she tells Julie Gould in the second episode of this six-part series about technology and scientific careers. “A colleague was using Python and R and I saw the potential.” What is her advice to other early career researchers who are keen to develop coding expertise?
Also, Brian MacNamee, an assistant professor in the school of computer science at University College Dublin, talks about the college’s data science course and how it can benefit both humanities and science students.
Finally, Nature technology editor Jeffrey Perkel describes how coding can help with computational reproducibility.
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Lara Schwartz is the director of the Project for Civil Discourse at American University where she’s also a professor in law and government. She’s also the coauthor of How to College: What to Know Before You Go (And When You’re There). We talk about the problem of false equivalence (also termed false balance, both-sidesism, and both-siderism) in the classroom, and how college professors can address this problem.
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Who tells the stories of science and who gets to learn from them? We’ve spent this year reckoning with inequity on all sides of research communication. From barriers that stop underserved communities from engaging with research, to biases that can exclude researchers from sharing their work. Listen to Dr. Sunshine Menezes, Executive Director of the Metcalf Institute at the University of Rhode Island, Professor Chris Jackson, Imperial College London, Sibusiso Biyela, a science communicator and columnist, and Lewis Hou, founder of Science Ceilidh discuss inclusive science communication.
And keep learning about these issues with the help of the resources below:
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Dr. Rodrigo Quian Quiroga is a Professor and Director of the Centre for Systems Neuroscience at the University of Leicester in the United Kingdom. He is also an author of the books Borges and Memory, Principles of Neural Coding, Imaging Brain Function with EEG, and The Forgetting Machine. Rodrigo is interested in understanding how memory works and how the brain works in general. He conducts experiments to determine how the neurons in our brain make us see, feel, make decisions, and remember the things we experience and learn in our lives. The memory research in Rodrigo’s lab investigates how memories are formed, stored, consolidated, and forgotten. Rodrigo also enjoys getting out of the lab to give his mind a break from thinking about experiments. In particular, he enjoys hanging out with his wife and kids, playing sports, and practicing Judo. Rodrigo received his undergraduate training in physics from the University of Buenos Aires in Argentina and was awarded his PhD in Applied Mathematics from the University of Luebeck in Germany. He was a postdoctoral fellow at the Research Center Juelich in Germany and he received a Sloan Fellowship to conduct research at the California Institute of Technology. Rodrigo also worked briefly at RIKEN in Japan and at the University of Nijmegen in The Netherlands. Rodrigo has received numerous awards and honors including the Royal Society Wolfson Research Merit Award, a Young Investigator Award from the American Epilepsy Society, and Rodrigo was also named one of 10 UK RISE Leaders in Science and Engineering in 2014. Rodrigo spoke with us about his experiences his career, research, and life.
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The pandemic has forced us all to adapt in various ways, for the sake of our physical or mental health. The stories in this week’s episode will focus on the ways in which our storytellers have forged new lives and routines for themselves.
Our first story is from Fiona Calvert, Story Collider UK producer and science communication officer at Alzheimer’s Research UK. Fiona has worked hard to manage her obsessive compulsive disorder, but when the pandemic begins, suddenly triggers are everywhere.
After Fiona’s story, our host interviews psychologist Dr. Kevin Chapman about how we can adapt to protect our mental health during this time.
Stay tuned for two more stories on Monday, from bestselling author Matthew Dicks and veterinarian Lauren Adelman! And see our website for transcripts and photos for all of our stories!
The podcast and artwork embedded on this page are from Erin Barker, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
We chat with Jess Wade (Imperial College London) about diversity issues in science, including her work increasing the profile of underrepresented scientists on Wikipedia and on getting more young women into science.
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After earning her PhD in Aerospace Engineering at Delft, Femke spent several years in oceanography, climate research, and subsurface modeling. She developed an expertise in data assimilation that she’s now applying to improve COVID-19 pandemic forecasting models.
Femke explains that data assimilation originated in weather forecasting, where a model is updated with the current day’s weather observations to provide a more accurate forecast for the next day. Data assimilation tools tune the model to provide a more accurate forecast. This concept can be applied in many areas including financial markets, the oil industry, and for COVID-19 research.
To help improve COVID-19 forecasting, she is using a compartmental model where there are compartments for different groups: those susceptible to COVID-19, those exposed to it, those infected, those who recovered, those in quarantine, and those who are deceased. The model is like a set of boxes, and the transition from one box to the other is governed by an ordinary differential equation. Then in those equations, you have parameters, which are typically not well-known.
The data assimilation approach is to work more from the “outside in” instead of from the “inside out”. So, if you know the number of people that have died since the start of COVID, then according to this data, you can determine what the parameters would have looked like three weeks ago. With this type of inverse modeling, you can actually tune the parameters in that compartment model, and find the most likely reproduction number or the likely number of infected in the first place. The approach of having these simple relationships between the different compartments is a good framework for a very complex process. However, you cannot expect the data to tell you the story if you don’t have any prior domain knowledge. In order to take their research to the next level, it will be critical for Femke and her colleagues to collaborate with the medical experts that built the models who know how to express certain relationships.
As she has transitioned from one field to another in her career, Femke has needed to learn how to apply her expertise to entirely different research areas. She says one of the most important skills she has developed is to ask a lot of questions and not worry about being wrong and she advises young researchers to do the same. Sometimes those questions can help people already in the field think differently, and lead to new insights.
Femke’s experience as an endurance athlete has also taught her valuable lessons for her work as a scientist. “People who excel in sports lose more races than they win. You have to make mistakes and fail, that’s the way you actually grow.” It also teaches you perseverance, to hang in there when it gets tough, and be happy with small increments of your own progress rather than always comparing yourself to your competitors.
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Breakout rooms, collaborative projects, games—whatever we do, it’s crucial that we do something to get our students talking to each other. In this episode, I’m giving you a huge list of ideas teachers have shared with me for getting students to interact better, both in-person and remotely.
Check out my new mini-course, Four Laws of Learning, and use the code LISTENER at checkout to take $5 off course tuition.
The podcast and artwork embedded on this page are from Jennifer Gonzalez, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
