PhD position Statistical Genetics / Machine Learning

University Medical Center Schleswig-Holstein (UKSH); Deutschland; Vor Ort; EUR 50.000 - 60.000; Vollzeit

Zusammenfassung

A leading university hospital in Germany is seeking a PhD student to join the Biomedical Informatics and Genetic Phenotype Redefinition Research Group. The role involves developing methods for analyzing large-scale genomic data and completing a PhD at Kiel University. Ideal candidates should have a Master's degree in a relevant field and skills in statistics and programming. This position offers a competitive salary and a collaborative research environment, with a commitment to supporting work-life balance.

Leistungen

Competitive salary according to TV-L E13

Access to biobank-scale datasets

Opportunities for conference participation

Flexible working hours

Qualifikationen

• Strong quantitative focus in bioinformatics, computer science, statistics, or mathematics.
• Foundation in statistics and machine learning including supervised learning and model evaluation.
• Experience with genomic data analysis, GPU programming or software development is a plus.

Aufgaben

• Develop and apply computational methods for genomic and phenotypic datasets.
• Analyze data from biobanks and clinical information systems.
• Contribute to teaching activities in the Medical Life Sciences program.
• Complete your PhD at Kiel University.

Kenntnisse

Statistical methods

Machine learning

Bioinformatics

Programming in Python

Programming in R

Ausbildung

Master’s degree in bioinformatics, computer science, statistics, or related field

Tools

Linux/HPC environments

Jobbeschreibung

Overview

The University Medical Center Schleswig-Holstein is one of the largest university hospitals in Europe with more than 80 clinics and institutes. It offers outstanding medical treatment and excellence in research and education with more than 16,000 employees. We provide top research at the interface of medicine, science and technology and maintain research co-operations with universities all over the world.

The Biomedical Informatics and Genetic Phenotype Redefinition Research Group at the Institute of Clinical Molecular Biology (IKMB), Kiel University (CAU) and the University Medical Center Schleswig-Holstein (UKSH), is seeking a PhD student with a strong background in statistics, machine learning (ML)/artificial intelligence (AI), or bioinformatics. Our group develops novel computational and statistical methods for the analysis of large-scale genomic, clinical, and phenotypic data, including phenome-wide association studies (PheWAS), statistical genetics, and precision medicine applications. This includes the development of scalable software tools and pipelines, potentially leveraging GPU/FPGA accelerators. Our aim is to build next-generation molecular atlases for chronic diseases and to improve patient stratification for personalized prevention, diagnosis, and therapy. We collaborate closely with the Department of Computer Science (CAU), the Comprehensive Center for Inflammation Medicine (CCIM), and the Competence Centre for Genomic Analysis (CCGA). As part of the cluster of excellence “Precision Medicine in Chronic Inflammation” (PMI), our group has published more than 100 peer-reviewed publications, including numerous high-impact articles in statistical genetics, biomedical data science, bioinformatics, and genomics.

Start in our team: Join our team and support us as soon as possible, initially on a fixed-term contract for 3 years, with the possibility of extension subject to performance and funding availability.

Your tasks

• Develop and apply computational, statistical, and ML-based methods for large-scale genomic and phenotypic datasets (e.g., PheWAS, statistical genetics, prediction models)
• Analyze high-dimensional data from biobanks and clinical information systems
• Contribute to teaching activities in the Medical Life Sciences program
• Complete your PhD at Kiel University (CAU), with a doctoral degree awarded either through the Faculty of Engineering or the Faculty of Mathematics and Natural Sciences, depending on your academic background and preference

Your profile

• Master’s degree in bioinformatics, computer science, statistics, mathematics, or a closely related field with a strong quantitative focus on these fields
• Solid foundation in statistics and/or machine learning, e.g., supervised learning, regression modeling, model evaluation, or high-dimensional data analysis
• Good programming skills in Python and/or R; experience with Linux/HPC environments is an advantage
• Experience with genomic data analysis, high-performance computing, GPU programming, or software development is a plus
• Excellent English communication skills and strong ability to work collaboratively

We offer

• Competitive salary according to TV-L E13 (75%), subject to collective bargaining regulations
• An interdisciplinary, data-rich research environment with access to biobank-scale genomic datasets and state-of-the-art technologies
• Close collaboration with computational experts, core facilities (Genomics and Bioinformatics), and partners within the PMI Excellence Cluster
• Opportunities for conference participation, workshops, and advanced training
• Flexible working hours and support in balancing work and family life

The UKSH has been certified as a family-friendly institution and is committed to further improving the compatibility of work and family life. We support the employment of disabled persons. Persons with disabilities will, with appropriate qualifications and aptitudes, be employed preferentially. The UKSH has set the goal to reach professional equality between men and women. The University aims to increase the number of women among the faculty staff and therefore explicitly encourages the application of female scientists.

Additional information

Please submit your application until 30th January 2026, indicating the reference number 27697, via our online portal:

Apply now via
https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/

For more information visit: www.uksh.de/jobs | https://www.ikmb.uni-kiel.de
Location: Kiel

Reference number: 27697

Your contact persons:
David Ellinghaus, phone: [phone]
Recruiter: Bianca Heil, phone: [phone]

Universitätsklinikum Schleswig-Holstein
Human Resource Management | Recruiting Center