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Deep Learning Engineer for Omics Data (f/m/x)   Wiss2607-16 | Institute for Genetics and the Cluster of Excellence for Aging Research (CECAD)
University of Cologne

Deep Learning Engineer for Omics Data (f/m/x) Wiss2607-16 | Institute for Genetics and the Cluster of Excellence for Aging Research (CECAD)

2026-08-27 (Europe/Berlin)
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Sobre el empleador

University of Cologne has 6 Faculties covering a broad spectrum of disciplines & has developed internationally outstanding research profile areas o...

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Faculty of Mathematics and Natural Sciences
Deep Learning Engineer for Omics Data (f/m/x)
Institute for Genetics (IfG) and the Cluster of Excellence for Ageing Research (CECAD)

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 Deep Learning Engineer (f/m/x) to support the team in the study of genomes and how they change with ageing and in cancer development. This is a core-funded position with a strong collaborative focus and the goal to build up deep learning infrastructures on Omics data for the lab and beyond.

YOUR TASKS

  • Working closely with other lab members to convert theoretical concepts into practical code
  • Providing technical guidance to junior members and interns
  • Implementing and evaluating state-of-the-art machine learning and deep learning techniques and algorithms, with a strong focus on omics data
  • Devising and testing new algorithms, often moving from academic papers to working code
  • Creating internal tools to speed up research, such as automated evaluation frameworks, data annotation tools, or specialized libraries

YOUR PROFILE

  • PhD in Computer Science, Bioinformatics, Artificial Intelligence or a related field or equivalent experience level
  • Solid understanding of machine learning fundamentals, including common algorithms, model training and evaluation techniques
  • Experience with Python programming and at least one AI/ML framework(e.g. Tensor Flow, PyTorch)
  • Exposure to data science concepts such as data preprocessing, feature extraction, and exploratory analysis
  • Exposure to biomedical data science
  • Curiosity and willingness to explore emerging AI domains in the biomedical domain
  • Very good interpersonal and communication skills; in particular, the ability to effectively work in a diverse, collaborative and interdisciplinary research environment
  • Fluency in English - written and oral (German is not required)

WE OFFER

  • Opportunity to receive training in cutting-edge methods using deep learning on genomics data and their integration
  • A diverse working environment with equal opportunities
  • Support in balancing work and family life
  • Flexible working time models
  • Extensive advanced training opportunities
  • Occupational health management offers

The University of Cologne promotes equal opportunities and diversity. Women will be considered preferentially in accordance with the Equal Opportunities Act of North Rhine-Westphalia (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 until 30 September 2028 with the possibility of an extension. If the applicant meets the relevant wage requirements and has the appropriate personal qualifications, the salary is based on remuneration group 13 TV-L of the pay scale for the German public sector.
Please apply online with proof of the required qualifications and a motivation letter (without a photo) under https://jobportal.uni-koeln.de. The reference number is Wiss2607-16. The application deadline is 27 August 2026.
For further inquiries, please contact Professor Dr Anna Poetsch ([email protected]) and take a look at our FAQs.

DESCRIPCIÓN DEL PUESTO

Título
Deep Learning Engineer for Omics Data (f/m/x) Wiss2607-16 | Institute for Genetics and the Cluster of Excellence for Aging Research (CECAD)
Ubicación
Abertus-Magnus-Platz Colonia, Alemania
Publicado
2026-07-31
Fecha límite de aplicación
2026-08-27 23:59 (Europe/Berlin)
2026-08-27 23:59 (CET)
Tipo de trabajo
Guardar trabajo

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