PhD Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)

Stellendetails zu: Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)

• Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)
• Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)
• Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)
• Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)
• Ph D Position in AI-based therapy validation based on fluorescence microscopy (f/m/x)

The group of Prof.

Dr.

Constantin Pape at the Institute of Computer Science, University Göttingen, invites applications for a research position (TV-L E13 100 %) on AI-based therapy validation based on fluorescence microscopy.

The position is part of the SFB1690, a DFG-funded research consortium that investigates the mechanisms underlying sensorimotor deficiencies such as hearing and vision impairments to enable future therapy development.

The starting data is as soon as possible.

Fluorescence microscopy is one of the most important experimental techniques for investigating the morphology of sensorimotor organs and for preclinical therapy validation.

Modern microscopes can image full organs, for example the complete cochlea, providing a very detailed picture of cellular morphology in tissue context.

However, the large amount of data acquired by these methods is difficult to analyze, creating the need for AI-based solutions, such as Cochlea Net, a dedicated analysis platform for the cochlea (see also the figure below).

The Ph D candidate will implement AI-based image analysis for the inner ear, including the cochlea and the vestibular system, and for organoid systems that mimic the inner ear.

He/she will use these methods to study the morphology of healthy and deficient organs with unprecedented detail, contributing to an improved understanding of disease mechanisms.

The candidate will also develop methods to preclinically validate gene therapy products that target hearing deficiencies.

This work will be pursued in close collaboration with project partners that research disease mechanisms and therapies.

AI-based cochlea analysis: A cochlea imaged in 3D with a high-resolution light sheet microscope (left), with stained spiral ganglion neurons (SGNs, red) and inner hair cells (IHCs, blue) together with the AI-based segmentation of SGNs and IHCs (right).

Your Profile

• Master degree in Computer Science, Computational Biology, Bioinformatics, Applied Mathematics, Physics, Biophysics, or a similar qualification.
• Experience with AI / machine learning.
• Proven programming skills, particularly in Python and experience with deep learning libraries (e. g. Py Torch).
• Proven competence in English, both written and spoken.
• A willingness to learn and extend this knowledge and master new challenges in the context of the research project.
• The ability to work independently and within an interdisciplinary team.
• A high level of critical thinking.
• Previous experience with relevant techniques (fluorescence microscopy, biomedical imaging, microscopy image analysis) is a plus.
• We Offer
• Research at the cutting edge of AI for microscopy image analysis.
• Possible applications in therapy development and other clinical impact.
• Access to cutting-edge HPC infrastructure, including GPU clusters with NVIDIA A100 and H100 GPUs.
• A full time position (100%) for up to three years, with the goal of obtaining a doctorate.
• Integration within a highly motivated interdisciplinary team.
• Flexible working hours.
• Institute with an outstanding working environment.
• Support in career development.

This role requires a regular on-site presence in Göttingen; remote work is possible to a limited extent.

The University of Göttingen is an equal opportunity employer that places particular emphasis on fostering career opportunities for women.

Qualified women are therefore strongly encouraged to apply for positions in fields in which they are underrepresented.

The university is committed to being a family-friendly institution and supports its employees in balancing work and family life.

The university is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled people.

In the case of equal qualifications, applications from people with severe disabilities will be given preference.

A disability or equality is to be included in the application in order to protect the interests of the applicant.

All applications received before April 1st, 2026 will receive full consideration, but the position will remain open until filled.

Please note: With submission of your application, you accept the processing of your applicant data in terms of data-protection law.

Further information on the legal basis and data usage is provided in the https://uni-goettingen. de/GDPR

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