PhD Student (gn*) Machine Learning

Universität Münster; Münster; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading research institution in Nordrhein-Westfalen is seeking a talented individual for a research position in the field of medical informatics. The role focuses on developing innovative machine learning methods for biomedical data analysis. A Master's degree in Computer Science or a related discipline is required, along with knowledge of algorithm development and bioinformatics pipelines. The successful candidate will work within an interdisciplinary team on complex disease processes. Competitive salary and professional development opportunities are offered.

Leistungen

State-of-the-art computing infrastructure

Structured PhD-training programme

Competitive salary and company pension plan

Qualifikationen

• Master’s degree in Computer Science, Bioinformatics, Medical Informatics, or related discipline is required.
• Knowledge of algorithm development and bioinformatics pipelines is essential.
• Initial experience in analyzing biological data, especially omics, is beneficial.

Aufgaben

• Develop innovative machine learning methods for biomedical data.
• Contribute to design of novel algorithms for large-scale omics datasets.
• Participate in Integrated Research Training Group.

Kenntnisse

Machine learning

Bioinformatics

Algorithm development

Data analysis

Good communication skills in English

Knowledge of workflow management systems

Ausbildung

Master’s degree in Computer Science or related discipline

Tools

Snakemake

Jobbeschreibung

Job Id: 11715

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

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 bioinformatics service unit of 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, Bioinformatics, Medical Informatics, Computational Biology, or a related discipline
• Knowledge of algorithm development and bioinformatics pipelines
• Initial experience in the analysis of biological data (e.g., omics technologies) is desirable
• Knowledge of workflow management systems (e.g., Snakemake) is beneficial
• High motivation for scientific work and willingness to contribute to an interdisciplinary team
• Excellent 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: [e-mail], T [phone]

Apply now via our career portal by 11 February 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