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# Biomedical Data Manager

- **Company:** Universität zu Köln
- **Location:** Köln, Germany
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Big Data, Bioinformatics, File Systems, Information Lifecycle Management, Python (Programming Language), Machine Learning, Data Classification, Storage Technologies
- **Published:** September 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=be447b2290e91200

## About the Role

» 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

## Description

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


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