Job Description

PhD student computational neuroscience / biophysics / machine learning (f/m/d)

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Faculty of Medicine, Department of Data Science, Hertie AI, index number 6831

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Part-time

75 %

Limited:

3 years*

Start of work:

01.01.2026

Application deadline:

21.11.2025
possibility of extension*

Tasks

Develop and train biophysical neuron models for retinal neurons in JAX using the Jaxley simulator Develop framework to quantify energy consumption in the retina Integrate biophysical retina models with deep reinforcement learning framework for understanding efficient coding in the retina Work with experimental researchers to contribute to understanding of the evolution of cell types in the retina Contribute to project management, teaching and grant writing

Profile

MSc in computational neuroscience, machine learning or related fields Prior publications at conferences / in journals are a plus Interest and track record in a data-driven approach to biophysics of neurons, neural coding or reinforcement learning Experience in developing open source packages, training models in JAX or related frameworks Curiousity, excellent analytical and communication skills Interest to work in a diverse and international team

Benefits

Work in the diverse environment of a modern university hospital, which, in addition to patient care, also focuses on medical research and teaching A future-proof job and location, as well as attractive compensation including a company pension plan (VBL), with the greatest possible flexibility in working hours Subsidy for public transport tickets and attractive discounts on our employee service platforms Structured onboarding phase, hospital-owned academy for developing professional, social, and methodological skills Healthcare through a wide range of sports activities

About us

The Faculty of Medicine is one of the four founding faculties of the Eberhard Karls University of Tübingen. With its non-clinical facilities as well as its research and teaching area corresponding to the organisational units of the University Hospital, it is one of the largest medical training and research institutions in Baden-Württemberg.

About the Department of Data Science, Hertie AI

Funded by the Hertie Foundation, the Hertie Institute for AI in Brain Health, part of the Medical Faculty of the Eberhard Karls University in Tübingen, Germany, focuses on the development of machine learning algorithms to improve the understanding, early detection and treatment of diseases of the nervous system. We are interested in using machine learning and data science approaches to better understand the healthy and diseased eye and to improve the diagnosis of ophthalmological diseases. We are uniquely positioned at the intersection of machine learning and medical research in Tübingen. The PhD position is part of the international Research Training Group limits2vision (https://limits2vision.net/) in collaboration with the Institute de la vision in Paris. We offer a structured PhD program with the opportunity to develop your individual skillset, intensive support, mentoring and career development. A key component in our program are student secondments at the respective partner institute.

As a member of the Cluster of Excellence "Machine Learning for Science" and the Tübingen AI Center, we are part of the vibrant machine learning ecosystem in the Tübingen area. At the same time, our location at the University Hospital of Tübingen allows us to maintain strong clinical collaborations. Our group has diverse backgrounds and origins and includes more than 10 different nationalities.

Contact for questions

Mr. Prof. Philipp Berens

hertieai@medizin.uni-tuebingen.de

Online Application to

Mr. Prof. Philipp Berens

Index number:

6831

Please apply through the application portal including CV and a cover letter.

Application deadline:

21.11.2025

Apply now

Apply via WhatsApp

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We offer remuneration in accordance with TV-L (collective wage agreement for the Public Service of the German Federal States), severely handicapped persons with equal qualifications are given preferential consideration. Interview expenses are not covered. Please note the applicable vaccination regulations.


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