Event Calendar

 
Lecture

A Scientist’s Primer on Mental Health

Friday, 17 April 2026, 15:45-17:30
Otto Lehmann Lecture Hall, CS
© OpenAI

Mental health is often misunderstood, especially in academia. Myths about what causes psychiatric conditions, who is affected, and how these challenges show up can create barriers to support and open conversation. Yet research shows that mental health struggles, from anxiety to depression, are far more common in academic and scientific communities than many realize.

Join us for this seminar and facilitated discussion, designed for researchers, by researchers. We’ll explore:

  • the prevalence of mental health illness in general and academic populations 
  • signs and symptoms, highlighting those seen in academic settings
  • the science underlying the causes and treatments of mental illnesses, with an emphasis on depression and anxiety (most common mental illness)

Together, we will identify gaps, barriers and opportunities for support at your institute. The discussion will be shaped by your questions and experiences, and we’ll measure knowledge before and after to ensure the conversation leaves you with actionable insights.

Costs/ Payment
KSQM covers the cost for this event.
Speaker
Hanna Sänger, Mental Health Counsellor & Coach

Dragonfly Mental Health
Organizer
Dr. Yu Goldscheider
Institut für Theoretische Festkörperphysik/Garst
KSQM/KIT
Wolfgang-Gaede-Str. 1
76131 Karlsruhe
Tel: 072160846030
Fax: 072160847040
Mail: ksqm does-not-exist.kit edu
https://www.ksqm.kit.edu/index.php
Targetgroup
Scientific Staff
Online registration
Please reigster here ASAP if you are KSQM member. If not, please write an email to yu goldscheider does-not-exist.kit edu.
Online Registration

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Timeline

Find an overview of past events in our timeline.

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About KCDS

Concept of the graduate school KCDS
KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in the field of model-driven and data-driven computational science.
In this unique program, doctoral researchers will be able to conduct an interdisciplinary research project that revolves around computational methods such as mathematical models, simulation methods and data science techniques, all the while building bridges between mathematical sciences and an applied SEE discipline (science, economics and engineering).
Addressing global challenges, the school provides a wide variety of topics, from meteorological ensemble forecasting to machine learning in elementary particle physics.
At KCDS, doctoral researchers have one supervisor from the mathematical sciences and one from the applied discipline. They are part of a dynamic community and participate in the school’s interdisciplinary training program, including hands-on training in small groups, summer schools, networking events and hackathons/datathons.
Thinking simulations and data together, we are ready to conquer the data-driven challenges of tomorrow!

Coordination Office