Research at the University of Tübingen The Eberhard Karls Universität Tübingen is an international and interdisciplinary research institution and has been awarded the status of a University of Excellence . Tübingen houses three internationally recognized research clusters in cancer immunology ( iFIT ), machine learning ( ML ), and infection medicine ( CMFI ). The University Hospital has a strong track record in translational research and houses innovative clinical centers (Comprehensive Cancer Center, German Cancer Consortium, National Center for Tumor Diseases).
At the newly established Systems Immunology Lab (Dr. Florian Wimmers), we leverage this unique infrastructure to answer questions in fundamental and translational immunology using cutting-edge systems biology and machine learning approaches. Our goal is to develop innovative therapies for cancer patients and provide a nurturing environment for students to explore and grow their interests and abilities. Our work is supported by an
ERC Starting Grant, the
DFB Emmy Noether program, and the
iFIT cluster of excellence.
Get in touch with us if you want to make essential discoveries impacting global health.
Key publications - Wimmers F, Pulendran B. Emerging technologies for systems vaccinology - multi-omics integration and single-cell (epi)genomic profiling. Curr Opin Immunol 2020.
- Wimmers F, et al. The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination. Cell 2021.
- Wimmers F, et al. Multi-omics analysis of mucosal and systemic immunity to SARS-CoV-2 after birth. Cell 2023.
PhD student (m/f/d) AI Modeling of Drug-Vaccine Interactions Using Large-Scale scRNAseq Data
Activities and responsibilities
We are seeking a highly motivated Postdoctoral Researcher to develop AI models analyzing drug-vaccine interactions in cancer immunology. Using large-scale scRNA-seq data, you’ll predict how cancer medications impact vaccine responses and generate virtual vaccination models. Ideal candidates have expertise in computational biology, machine learning, and data analysis, with a focus on immunology or oncology. Importantly, you will be able to collect experience with wet-lab and computational work (currently a rare but highly demanded type of scientist). Your primary responsibilities will be:
- Design, implement, and optimize AI models to analyze large-scale scRNA-seq datasets (>3 mio cells)
- Process, clean, and interpret complex scRNA-seq data to identify biological patterns and insights
- Work closely with wet-lab researchers to integrate computational findings with experimental data
- Cooperating with partners in Tübingen and within our international network (US, CH, NL)
Qualification profile
- Master’s degree in Bioinformatics, Machine Learning/AI, Biochemistry, or related disciplines
- Hands-on experience in using Machine Learning or AI approaches to extract meaningful information
- Passion for immunology, systems biology, and biomedical research
- Enthusiastic learning and collaborative working attitude are a must
- Excellent oral and written communication skills
We offer
- A diverse and challenging job with a stimulating, high-profile research project
- Three-year fully funded postdoc position (remuneration according to TV-L salary scale 13)
- Training in wet-lab and computational work & intensive mentoring within our team
- Excellent genomics and computational infrastructure in a thriving biotech & machine-learning hub
- Make one of the most picturesque, enjoyable, and ecological towns your home (BBC & ZEIT)! Tübingen has a long history of academic excellence (founded in 1477; DNA< was discovered here; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning.
How to apply: Please send your CV, a cover letter motivating your interest in the position, and the name and address of 3 references to Dr. Florian Wimmers (email). Also, find more information on our group on our website: https://www.thewimmerslab.com/