Postdoctoral researcher in machine-learning for multi-omics (f/m/d)

Location:

• Berga-Wünschendorf Uni Heidelberg Jetzt bewerben

Summary

• Working Time: Full-time
• Type: n/a
• Qualification Level: B

Desired Skills & Knowledge

• Machine Learning
• Storage
• Across
• Test Execution
• Big Data Analytics
• Translation Software
• Data Analysis
• Mobile App
• Engagement

Our Benefits

• Home office

Job Description

Heidelberg University is a comprehensive university with a strong focus on research and international standards. With around 31,300 students and 8,400 employees, including numerous top researchers, it is a globally respected institution that also has outstanding economic significance for the Rhine-Neckar metropolitan region.

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.

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

Contact

• A stimulating research environment within the Institute and at Heidelberg University (https://www.hdsu.org)
• Home office opportunity

Remuneration is based on the German wage agreement for the public service (TV-L).

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: carl.herrmann@uni-heidelberg.de. The application deadline is February, 20th 2026. carl.herrmann@uni-heidelberg.de)

Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply. Persons with severe disabilities will be given preference if they are equally qualified. Information on the job advertisements and the collection of personal data is available at www.uni-heidelberg.de/en/job-market.

Profile

Professional Requirements

• Coaching and Mentoring
• Data Integration
• Genomics
• Infrastructure
• Machine Learning
• Oncogenomics
• Personalized Medicine
• Postdoc
• Statistics
• Public Service

Personal Skills

• Communication
• Teamwork

Education

• Dissertation

Language Skills

• English

Application

Jetzt bewerben

Industry:

Healthcare / Social Services

Employer:

Uni Heidelberg

Address:

Uni Heidelberg Kurfurstenweg 14 69412 Eberbach

Web:

http://www.hdsu.org, www.uni-heidelberg.de