Heidelberg University Postdoctoral Researcher in Machine Learning for Multi-omics 2026

The department of Bioinformatics at the Institute of Pharmacy and Molecular Biotechnology (IPMB) of Heidelberg University is offering a 3-year full-time (100%; 39.5 h/week) postdoc position in Multiomics Data Integration and Machine-Learning for therapy response prediction in metastatic cancer. This position is funded by the European Partnership in Personalized Medicine (EP PerMed) within a trans-national consortium involving research groups from Spain, Italy, France and Germany, focusing on metastatic papillary renal carcinoma.
The consortium will perform multi-omic characterization of metastatic pRCC samples across four European countries, integrating real-world drug response data with preclinical model testing to create the world′s largest metastatic pRCC database. Heidelberg University leads the multidimensional data integration task, focusing on centralized data management and machine learning-based integration of multi-omic datasets. Our goal is to identify predictive signatures and develop treatment response models to enable biomarker-guided clinical trials.

Your tasks:

• Apply interpretable machine learning approaches to identify multi-omic signatures and build predictive models for treatment response.
• Establish and maintain centralized storage infrastructure for processed multi-omic datasets from consortium partners and community use.
• Collaborate with clinical and experimental partners across multiple countries.

Table of Content

• Summary
• Benefits
• Requirements
• Application Deadline
• How To Apply

Summary

• Application DeadlineFebruary 20, 2026
• Study LevelPostdoctoral Fellowships
• SponsorHeidelberg University
• City to studyBaden-Württemberg
• School to studyHeidelberg University
• Eligible CountryAll Countries

Benefits

• Position in cutting-edge precision medicine research with international collaborators
• Access to unique multi-omic datasets and computational infrastructure
• A stimulating research environment within the Institute and at Heidelberg University (https://www.hdsu.org)
• Home office opportunity

Requirements

• PhD in Bioinformatics, Computational Biology, Statistics, Computer Science, or related field
• Experience with high-throughput genomic data analysis
• Experience in machine learning and statistical modeling for genomic data
• Excellent English communication skills and team work skills
• Experience with multi-omics data integration and cancer genomics would be a plus

Check also:
2026 Fully Funded Humboldt Research Fellowship
2026 Konrad Adenauer Foundation Scholarship

Application Deadline

How To Apply

• Please send a PDF of your CV, including up to five publications if available, and a one-page motivation letter including at least two references in one collated PDF file to: [email protected]

For more information, kindly visit Heidelberg University scholarship webpage.