Learn how to develop machine learning models, how to apply them to toxicological data, and how to interpret the results.
Registration No fees for the school*
*you will only have to pay for your own supplies, accommodation and food.
We know machine learning, we know biology.
Our research careers evolve around creating data for machine learning and employing that data predictively. We will teach you how to do the same.
As one of the fathers of bioinformatics, Burkhard adopted machine learning early to predict various protein properties.
Ivan's research revolves around integrating AI into toxicology in new and innovative ways.
Kyra applies machine learning for protein analysis, developing predictive models and data-driven insights for biomedical research.
Luisa is investigating the effects and applications of bacterial toxins using data science and molecular biology techniques.
Sebastian is creating reproducible and easy-to-learn machine learning frameworks.
Tanja is using Machine Learning to predict bacterial exotoxins in her research.
Tobias is researching how to make machine learning accessible for protein scientists.
Tobias is researching machine learning approaches to study toxin structure & function evolution.
The target audience for this machine learning school are toxinologists and generally biologists who are curious to learn the basics of machine learning and how to integrate machine learning into their day-to-day work.
We’re currently aiming at around 16 participants.
Of course, we try to offer a well-rounded program that also contains relaxing activities around the area.
We recommend to find a place near Garching to minimize travel time. Other than that, we cannot provide any accommodation support.
If you have any questions, please do not hesitate to reach out to us.