PhD Student / Machine Learning Specialist (gn)

PhD Student / Machine Learning Specialist (gn

Fixed term of 3 years | Full-time with 100% | Salary according to TV-L E13 | Institute of Medical Informatics | Job ID : 11715

We are UKM. We have a clear social mission and, with our focus on healthcare, research, and teaching, we bear a unique responsibility - ideally with you on board!

The position is based at the Institute of Medical Informatics within the research group Machine Learning for Biomedical Data led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction . The CRC 1748 involves scientists of the University, University Hospital, and Max Planck Institute Münster as well as of the RWTH Aachen. Our central objective is to elucidate the genetic, molecular, and cellular mechanisms governing the formation and function of the testis, production and function of sperm, fertilisation, as well as early embryonic development - in both health and disease. To this end, we combine interdisciplinary research in molecular, structural, and cell biology as well as in physiology, biophysics, epi / genetics, (bio)informatics, and multimodal data analysis.

The research group of Dominik Heider focuses on machine learning and data-driven methods for addressing biomedical questions of high clinical relevance, with an emphasis on innovative approaches to complex disease processes and large-scale omics data analysis.

RESPONSIBILITIES :

Developing innovative methods from the field of machine learning for biomedical data, e.g., explainability, interpretability, and causal inference

Contributing to the design of novel algorithms and models for the analysis of large-scale omics datasets

Multi-modal machine learning model development and data integration

Participating in the Integrated Research Training Group "Reproduction.MS PhD-Training Centre in Translational Science"

REQUIREMENTS :

Master’s degree in Computer Science, Data Science, Medical Informatics, or a related discipline

Knowledge of machine learning, statistics, and algorithm development

Experience in the analysis of biological data (e.g., omics technologies) is desirable

Programming skills (e.g., Python, R, C / C++)

Motivation for scientific work and willingness to contribute to an interdisciplinary team

Good English communication skills (spoken and written); German skills are advantageous

WE OFFER :

State-of-the-art computing infrastructure

Competitive, interdisciplinary, and international research environment with a track record of intense mutual collaboration

Structured PhD-training programme with a wide range of professional development opportunities

Salary according to tariff agreement, extra annual payment, and company pension plan (VBL)

A respectful and appreciative work environment within a diverse team

For inquiries, please contact : Dominik.Heider@uni-muenster.de , T +49 251 83 58381.

Apply now via our career portal by February 11, 2026.

Please include :

Letter of motivation (max 2 pages)

Summary of your Master‘s thesis (max 1 page)

Transcript and scanned copies of your degree certificates

Two letters of recommendation and / or names and contact details of two references

BENEFITS

Exciting Projects

Professional Development and Training

Interdisciplinary Collaboration

Part of Research Innovation

Additional Benefits

Exciting Projects

Professional Development and Training

Interdisciplinary Collaboration

Part of Research Innovation

Additional Benefits

• gn=gender neutral)

The University Hospital of Münster is one of the leading hospitals in Germany. Such a position cannot be achieved by size and medical successes alone. The individual commitment counts above all. We need your commitment so that even with little things we can achieve great things for our patients. There are many possibilities open for you so that you may develop with them.

Questions about how to apply? Click here

Equal opportunities are a part of our Human Resources Policy. UKM supports the compatibility of work and family life and is certified as "Family-friendly Company" since 2010. Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference. Due to legal requirements working with us is only permitted with complete vaccination against measles.

Universitätsklinikum Münster

Albert-Schweitzer-Campus 1, Gebäude D5

48149 Münster

www.ukm.de