New "I am Scientist" Podcast episode about mental health of PhD students

As PhD students we often get asked, “Hey, how is your thesis going?”
This question can often create a lot of pressure even if it is well-intended. I had the great pleasure to discuss this topic with two of the authors of the paper that has been published in 2023 about the mental health of PhD students. 
Julian Friedrich and Markus Kleinhansl are part of the PhD initiative “Sustainability” in Tübingen, which has actively engaged in various sustainability projects. They also created a survey focusing on the working habits and mental health of PhD students. They found, among other things, that 31.3% of the participants work 45 hours or more and that one third of the PhD students is at risk of major depression. During the podcast, we discuss the causes of stress among PhD students and how this pressure can sometimes lead to crisis situations. We also talk about practical techniques to manage stress and overcome the “imposter” feeling many of us experience.

I joined the “I AM SCIENTIST” podcast team last year. It was started by Daniel Hölle and Philipp Hubert, and since then, the three of us have had a lot of fun working together and grow this project. In the podcast, we interview PhD students about the science they are passioned about, their day-to-day life as researchers, and what personally drives them. All our efforts for this podcast happens in our freetime, and we (so far) only produce episodes in German for our listeners there.Recording this episode on mental health was an opportunity for me to raise awareness on important issues, reach more people, and make a difference.

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Lisa Schmors is a PhD student in the Department of Data Science at the Hertie Institute for AI in Brain Health at the University of Tübingen and an IMPRS-IS scholar , interested in computational neuroscience and statistical modelling. In her work, she uses statistical models to investigate cortico-thalamic feedback to contribute to a general computational model of visual processing in the mammalian brain. In addition, she utilizes clustering algorithms to identify different cell types in the lateral habenula, analyzing functional and morphological data.


Data Science

Research Group

Neuronal Modeling