Mots-Clés

multiomique cancer genomics machine-learning

Description

Postdoctoral Research Position in Multi-Omics Data Integration and Machine Learning in Cancer Genomics

• Position: Full-time postdoctoral researcher
• Institution: Universität Heidelberg, Institut für Pharmazie und Molekulare Biotechnologie, Department of Bioinformatics (Prof. Dr. Carl Herrmann)
• Duration: 36 months (Starting date: April 1st, 2026)

Project Overview

Papillary renal cell carcinoma (pRCC) is a heterogeneous kidney tumor with diverse molecular drivers. Metastatic pRCC is poorly understood and treated with antiangiogenic agents and immunotherapy lacking biological rationale, resulting in suboptimal outcomes and highlighting the need for personalized treatment strategies.
The pRCC-TREAT project is an international collaboration funded by EP PerMed (Spain, Italy, France, Germany). 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 WP4 (Multidimensional Data Integration), focusing on centralized data management and machine learning-based integration of multi-omic datasets. WP4 will identify predictive signatures and develop treatment response models to enable biomarker-guided clinical trials.

Your Role

As a postdoctoral researcher in WP4 (Multidimensional Data Integration), you will:

• 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

Your Profile

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

What We Offer

• Position in cutting-edge precision medicine research with international collaborators
• Access to unique multi-omic datasets and computational infrastructure
• Opportunities for publications and conference participation
• Competitive salary according to TV-L E13

Application until 15/02/2026
Upload CV, cover letter addressed to Prof. Dr. Carl Herrmann, and contact information for 2-3 references in a single pdf file indicating your name using this upload link