Your Twin learns with you

30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Philipp Berens profile picture

Philipp Berens

Has grant

Professor

University of Tübingen
Country flagGermany

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Recent Grants

Grant: Close

Cell type specific computations

Open Date: 2016-05-01

Close Date: 2021-05-01

Grant: Close

Emergence of retinal ganglion cell response diversity from synaptic interactions in the inner retina - a combined approach of two-photon population imaging and computational modeling

Open Date: 2015-01-01

Close Date: 2017-12-01

Positions (1)

Publisher
source

Philipp Berens

University Name
.

University of Tübingen

The University of Tübingen is offering a postdoctoral position in Fair AI and Oculomics for Global Health at the Hertie Institute for AI in Brain Health. This exciting opportunity is part of a DFG-funded project focused on developing de-biased and interpretable foundation models to reconstruct health history from fundus images, with a special emphasis on datasets from The Gambia. The project is a collaboration between the Hertie AI, the MRC Unit in The Gambia, and international partners, aiming to improve fairness and interpretability of AI in linking ocular images to systemic health variables. The successful candidate will join the Department of Data Science and work on developing and evaluating algorithmic strategies to detect and mitigate bias in foundation models using African fundus datasets. Responsibilities include designing and implementing interpretability techniques, co-developing deep learning pipelines for reconstructing systemic health conditions from fundus images, overseeing high-quality data collection and exchange between The Gambia and the University of Tübingen, and co-leading the project's strategic direction. The postdoc will also co-supervise a PhD student and disseminate research findings. Applicants should have a doctoral degree in computer science, medical informatics, physics, mathematics, or a related quantitative field with a focus on machine learning. A strong track record in developing and implementing deep learning algorithms for medical image analysis is required, with experience in foundation models or interpretability considered a strong plus. Advanced programming skills in Python and experience with deep learning frameworks such as PyTorch are essential. The role requires experience or strong potential in co-leading international research projects, coordinating complex data-sharing workflows, and excellent communication skills in English. A strong interest in Global Health and willingness to travel to The Gambia for data collection coordination are also important. The position is full-time (100%) for 36 months, with remuneration according to TV-L E13. The University of Tübingen offers a modern research environment, state-of-the-art technology, and excellent career prospects, with structured onboarding, diverse training opportunities, and active promotion of equality and diversity. Severely handicapped persons with equal qualifications are given preferential consideration. Interview expenses are not covered. For more information on salary, visit the university's career page. To apply, submit your CV and cover letter online via the University of Tübingen job portal, referencing index number 7258. For questions, contact Prof. Philipp Berens at [email protected]. The application deadline is March 8, 2026.

9 months ago

Articles (20)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Collaborators (7)

Pedro J. Gonçalves

Associate Professor

KU Leuven

BELGIUM
View details

Manuel Mameli

Full Professor

University of Lausanne

SWITZERLAND
View details

Jonathan Oesterle

University of Tübingen

GERMANY
View details

Laura Busse

Professor

Ludwig-Maximilians-Universität München

GERMANY
View details

J. Alexander Bae

Assistant Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA
View details

Thomas Euler

Professor

University of Tübingen

GERMANY
View details

Myriam Lipprandt

-

GERMANY
View details