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Doctoral Researchers: Up to 6 Fully Funded Positions in Data Science & Health 11.07.2025 Deutsches Krebsforschungszentrum (DKFZ) Heidelberg
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Doctoral Researchers: Up to 6 Fully Funded Positions in Data Science & Health
Heidelberg
Aktualität: 11.07.2025

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11.07.2025, Deutsches Krebsforschungszentrum (DKFZ)
Heidelberg
Doctoral Researchers: Up to 6 Fully Funded Positions in Data Science & Health
Über uns:
«Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts - whether in research, administration or infrastructure. This is what makes our daily work so meaningful and exciting. Do you want to bring artificial intelligence (AI) and data science to the forefront of health research? The Karlsruhe Institute of Technology is a top-ranked computer science university and Helmholtz research center. The German Cancer Research Center is the largest biomedical research institution in Germany with leading research in health data sciences. The Heidelberg University is the oldest university in Germany with a leading university clinic and excellent track record in scientific computing. These three top institutions joined to tackle this thrilling area by providing a unique doctoral program:
Aufgaben:
  • Imaging & Diagnostics
  • ID01: Robust knowledge discovery of cell interactions in multichannel imaging flow cytometry and live cell imaging
  • ID02: Close proximity human-robot interaction in medical interventions - combining robot control and data science approaches
  • ID03: Fragments filtration for helium radiography and computed tomography
  • ID04: Knowledge Graph Reasoning for Generalized Surgical AI
  • ID05: Multimodal decision support for postoperative monitoring after brain tumor surgery
  • ID06: Enhancing Biomarker Discovery through Covariate-Aware Multi-Omics Factorization Models
  • ID07: Data-based outlier detection and risk validation for multi-class prediction in newborn screening
  • Here you can find the abstracts and PIs of each project:
Qualifikationen:

We are looking for excellent graduates holding a master's degree, received by October 2025 at the latest, in computer science, mathematics, engineering, physics or related quantitative sciences (e.g. bioinformatics, medical informatics or robotics).

Wir bieten:
  • Cutting-edge research and working with top-experts in data science, AI, health and medicine
  • Inspiring work environment in an interdisciplinary setting
  • Integrated structured training curriculum of scientific and professional skills taught in English
  • Financial support for attending conferences and research collaborations
  • A contract for a fully-funded position with competitive salary according to the applicable regulations of the participating institutions (e.g. German E13 TVöD or TV-L) at one of the three HIDSS4Health research institutions
Unser Kontakt:
To apply for a position please visit https://www.hidss4health.de/application/ to fill in the required HIDSS4Health-specific application documents which need to be uploaded with your application. Https://www.helmholtz.de/assets/hidss4health/Dokumente/HIDSS4Health_Project_Abstracts_2025.pdf Dr. Daniel Walther Telefon: +49 6221 42-3018 Deutsches Krebsforschungszentrum | Im Neuenheimer Feld 280 | 69120 Heidelberg | www.dkfz.de
Weitere Informationen:
We are convinced that an innovative research and working environment thrives on the diversity of its employees. Therefore, we welcome applications from talented people, regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion and age. People with severe disabilities are given preference if they have the same aptitude. Notice: We are subject to the regulations of the Infection Protection Act (IfSG). Therefore, all our employees must provide proof of immunity against measles.

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