Ihre Aufgaben
- Analysis and integration of cancer multi-omics datasets (transcriptomics, epigenomics, drug-response data)
- Development of machine learning and AI models for biomarker discovery and prediction of treatment response
- Application and further development of graph-based learning methods enriched with biological pathway and drug–target knowledge
- Benchmarking of novel models against existing computational approaches
- Interpretation of results in close collaboration with clinical and experimental consortium partners
- Independent management of bioinformatics sub-projects and contribution to project coordination
- Preparation and submission of scientific manuscripts and reports
Ihre Qualifikationen
- PhD in Bioinformatics, Computational Biology, Computer Science, or a closely related field
- Proven experience in machine learning or deep learning applied to biomedical data
- Strong programming skills in Python, R, or similar languages
- Expertise in the analysis of large-scale omics datasets (e.g. transcriptomics, methylomics, drug-response data)
- Experience with graph-based methods or network biology is an advantage
- Track record of scientific publications appropriate to career stage
- Ability to work independently and lead projects, while collaborating effectively in an interdisciplinary team
Wir bieten
- An exciting research environment at the interface of bioinformatics, AI, and cancer medicine
- Structured mentoring and a supported onboarding process
- A diverse, interdisciplinary, and multi-professional working environment
- Access to state-of-the-art bioinformatics infrastructure and large-scale biomedical datasets
- Salary according to TV-L (part-time, 65%) for an initial period of 3 years, with the possibility of extension
- Additional occupational pension scheme (VBL)
- Company health management programme and sports facilities
- A position in Göttingen — a vibrant university city with a rich scientific tradition
Einleitungstext
The Department of Medical Bioinformatics at the University Medical Center Göttingen is a leading research group in the bioinformatic analysis of biomedical high-throughput data. Our work focuses on the development of biomarker signatures, statistical methods, and machine learning approaches for personalised and systems medicine.
We are embedded in multiple DFG- and BMBF-funded collaborative research projects, with a strong focus on the analysis of cancer omics data — including genomics, transcriptomics, and spatial transcriptomics — and the development of innovative AI and machine learning methods. We work in close collaboration with clinical and experimental partners in national and international research consortia.
