PhD Student for Machine Learning in Epilepsy and Behavior

Project Description

We are looking for a highly motivated and skilled PhD student to develop machine learning methods for automatic extraction of postural models and behavioral states, and their combination with physiological data in epileptic mice. This project is a collaboration with the startup StriaTech and the Hertie Institute for Clinical Brain Research. The candidate is expected to develop novel machine learning models for complex multimodal data to quantify the clinical manifestation and progression of neurodegenerative diseases in animal models and patients.

The ideal candidate has a degree in machine learning, physics, math, electrical engineering, or related fields, and a strong background in mathematics, machine learning, statistics, and ideally causal learning, with prior experience in working on life science/clinical data.

We offer a thriving and interactive environment in one of Europe’s leading location for machine learning, and the opportunity to directly work with clinicians and data from the large neurology section of Tübingen’s university hospital.

Tübingen is one of the leading locations for machine learning in Europe, offering a scientific inspiring and open enviroment to develop the intelligent systems of tomorrow. The International Max Planck Graduate School for Intelligent Systems is Germany’s largest graduate program for machine learning and related topics.

We particularly encourage women and other underrepresented groups in STEM fields to apply. Please check the How to apply section below.