UKSH - Universitätsklinikum Schleswig-Holstein

PhD (mfd) Statistical Genetics Machine Learning

Stellenbeschreibung:

Biomedical Informatics and Genetic Phenotype Redefinition Research Group
Institute of Clinical Molecular Biology (IKMB) Kiel University & UKSH

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.

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.

What we offer you:

  • 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

What you can expect:

  • 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 the 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:

  • Masters 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 look forward to receiving your application on quoting reference number 27697.

How to apply:

Please send your cover letter CV academic transcripts (BSc/MSc) and the names and contact details of two references as PDF (for technical reasons a maximum of 10 MB per uploaded pdf document)

Key Skills

  • Business Development
  • Customer Service
  • Attorney
  • CISSP
  • Data Analysis

Employment Type: Full Time

Experience: years

Vacancy: 1

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NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    20 Jan 2026
  • Standort:

    Kiel
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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