Postdoctoral Researcher: AI Modeling of Drug-Vaccine Interactions Using Large-Scale scRNA-seq Data

Postdoctoral Position: AI Modeling of Drug-Vaccine Interactions

We are seeking a highly motivated Postdoctoral Researcher to join our newly established Systems Immunology Lab (Dr. Florian Wimmers), developing AI models to analyze drug-vaccine interactions in cancer immunology. Our lab is at the forefront of systems immunology, utilizing cutting-edge omics and AI approaches to address key questions in vaccination.

As part of our team, you will work with large-scale scRNA-seq data from high-throughput drug screens using immunological organoids to predict how cancer treatments affect vaccine responses and create virtual vaccination models. This role offers a unique opportunity to gain experience in both computational and wet-lab work, a highly sought-after skillset in today’s scientific landscape.

Supported by an ERC Starting Grant, the DFG Emmy Noether Program, and the iFIT Cluster of Excellence, our lab provides a collaborative and innovative environment aimed at developing vaccination approaches and therapies for cancer patients. If you’re passionate about making impactful discoveries in global health, we encourage you to apply and be part of our dynamic team.

Key Responsibilities

• Design, implement, and optimize AI models to analyze large-scale scRNA-seq datasets (>3 mio cells, >3,000 conditions)
• Process, clean, and interpret complex scRNA-seq data to identify biological patterns and insights
• Work closely with wet-lab researchers to design organoid and scRNA-seq experiments and integrate computational findings with experimental data
• Cooperate with partners in Tübingen and within our international network (US, CH, NL)
• Interpret data, write manuscripts, and present findings at conferences and seminars.

 

Key publications

• Wimmers F, et al. Multi-omics analysis of mucosal and systemic immunity to SARS-CoV-2 after birth. Cell 2023. Link
• Wimmers F, et al. The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination. Cell 2021. Link
• Arunachalam P*, Wimmers F*, (Shared 1st) et al. Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans. Science 2020. Link
• Wimmers F, Pulendran B. Emerging technologies for systems vaccinology – multi-omics integration and single-cell (epi)genomic profiling. Curr Opin Immunol 2020. Link

 

Your 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

 

Benefits for you

• A diverse and challenging job with a stimulating, high-profile research project
• 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.

 

About Eberhard Karls Universität 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 and AI (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).

 

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 (molmed@ifib.uni-tuebingen.de). Please mention “Postdoctoral Position: AI Modeling of Drug-Vaccine Interactions” in your subject line.