Job Description
We are one of the largest and oldest universities in Europe and one of the most important employers in our region.
Our broad range of subjects, the dynamic development of our main research areas and our central location in Cologne
make us attractive for students and researchers from around the world. We offer a wide range of career opportunities in
science, technology, and administration.
The Poetsch Group is looking for a Biomedical Data
Manager (f/m/x) to support the team in its research on
genomes and their changes with age, as well as on the
development of cancer. The position focuses on the collab-
orative development of an infrastructure and workflow for
data analysis and the application of machine learning to a
wide range of datasets on somatic mutagenesis.
YOUR TASKS
» Designing and implementing standardized folder
hierarchies and naming conventions across
HPC storage systems
» Development of metadata schemas to enable efficient
data collection, retrieval, and data lifecycle management
for large quantities of data
» Collaborative implementation of standard operating
procedures for the analysis of genomic data, including
the application of machine learning and deep learning
» Development and implementation of guidelines for
the organization of personally sensitive data and
best practices for research teams
» Implementation of research projects in the field of
somatic mutagenesis and collaboration with researchers
» Advising Researchers on best practices for data
organization
» Developing documentation, templates, and standard
operating procedures
YOUR PROFILE
» Bachelor‘s or Master‘s degree in bioinformatics,
bioengineering, genetics, or a related field
» Strong experience with Linux/Unix command-line
environments
» Familiarity with HPC storage architectures and
parallel file systems
» Strong attention to detail and systematic approach
to data classification
» An understanding of scientific research processes in
genetics, data types in genomics, and the correspond-
ingly large volumes of data
» Excellent communication skills to work with diverse
technical and non-technical users
» Proficiency in Python and R for data analysis
» Experience with machine learning would be
advantageous
» Very good interpersonal and communication skills; in
particular, the ability to effectively work in a diverse,
collaborative and interdisciplinary research environment
» Excellent written and spoken English skills are an
essential requirement
WE OFFER
» Opportunity to receive training in cutting-edge methods
in bioinformatics, using also deep learning on genomics
data
» A diverse working environment with equal opportunities
» Support in balancing work and family life
» Extensive advanced training opportunities
» Occupational health management offers
» Flexible working time models
The University of Cologne promotes equal opportunities and
diversity. Women will be considered preferentially in accord-
ance with the Equal Opportunities Act of North Rhine-West-
phalia (Landesgleichstellungsgesetz – LGG NRW). We also
expressly welcome applications from all suitable candidates
regardless of their gender, nationality, ethnic and social
origin, religion, disability, age, sexual orientation and identity.
The position is available at the earliest possible time on
a full-time basis (39,83 hours per week). The position is
to be filled for a fixed term for 24 months. If the applicant
meets the relevant wage requirements and personal
qualifications, the salary is based on remuneration group
11 TV-L of the pay scale for the German public sector.
Please apply online in English with proof of the required
qualifications and a motivation letter without a photo under:
https://jobportal.uni-koeln.de.
The reference number is TUV2609-01. The application
deadline is 01 October 2026.
For further inquiries, please contact Professor Dr Anna
Poetsch (apoetsch@uni-koeln.de) and take a look at our
FAQs.
Biomedical Data Manager (f/m/x)
Faculty of Mathematics and Natural Sciences
Institute for Genetics (IfG) and the Cologne Cluster of Excellence on Aging and Aging-associated Diseases (CECAD)
