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Antonella Di Pizio

6 days ago

PhD Student in Molecular Modeling and AI-Guided Protein Structure Design for Food Systems Biology Leibniz Institute for Food Systems Biology at the Technical University of Munich in Germany

I am offering a PhD position in molecular modeling and AI-guided protein structure design for food systems biology at LeibnizLSB@TUM.

Leibniz Institute for Food Systems Biology at the Technical University of Munich

Germany

email-of-the@publisher.com

Jan 15, 2026

Keywords

Computer Science
Chemistry
Biology
Structural Biology
Computational Chemistry
Molecular Modeling
Molecular Docking
Protein Structure Prediction
Enhanced Sampling
Taste Receptor
Bioinformatics
Molecular Simulations
Data-analysis
Odor Perception
Ai-guided Protein Structure Design

Description

The Leibniz Institute for Food Systems Biology at the Technical University of Munich (LeibnizLSB@TUM) is a leading research center integrating biomolecular research, bioinformatics, and advanced analytical technologies to investigate the complex interactions between the human organism and food components. As part of the Leibniz Association, the institute offers a dynamic and interdisciplinary environment for cutting-edge research in food systems biology. The Molecular Modeling / Section III research group is seeking a committed PhD student to join a project focused on advancements in structural biology and AI-guided protein structure design. The research aims to elucidate the structures of receptors involved in food taste and odor perception, as well as food-derived proteins. Leveraging these structural insights, the project will pursue structure-based ligand design and develop predictive methods to identify novel food ingredients and flavor modulators. Key responsibilities include applying AI-based methodologies for protein structure prediction and conformational ensemble analysis, conducting molecular docking and cofolding studies, performing molecular dynamics simulations, and utilizing enhanced sampling techniques. The position offers a thorough induction, diverse training and development opportunities, and a collegial working atmosphere with flat hierarchies and short decision-making paths. Flexible working hours and the option for mobile working (home office) are available, along with a company pension scheme (VBL) and annual bonus payment. The ideal candidate will have a strong background in bioinformatics or computational chemistry, experience in data analysis, and solid English-language skills. Programming experience is highly recommended. Applicants should demonstrate a keen interest in the research topic, self-motivation, independence, excellent teamwork, and organizational skills. The institute is committed to equal opportunities, diversity, and a respectful working environment, welcoming applications from all backgrounds. Applicants with severe disabilities or equivalent status will be given preferential consideration in cases of equal qualification. The position is part-time (TV-L 13, 65%) and initially limited to 3 years, starting on 15 January 2026. For further information about the research group, visit the Section III webpage. To apply, send your comprehensive CV, transcripts, and names of three potential references as a PDF file, stating the reference number 2025-17-S3-ADP, via email to recruiting.leibniz-lsb@tum.de. For questions, contact Prof. Dr. Antonella Di Pizio at a.dipizio.leibniz-lsb@tum.de. Join a motivated team at the forefront of non-university research in food systems biology and contribute to innovative projects that bridge molecular modeling, AI, and food science.

Funding

Available

How to apply

Send your application, including a comprehensive CV, transcripts, and names of three potential references, as a PDF file and stating the reference number 2025-17-S3-ADP via email to recruiting.leibniz-lsb@tum.de. For questions, contact Prof. Dr. Antonella Di Pizio at a.dipizio.leibniz-lsb@tum.de. More information about the research group is available online.

Requirements

Applicants should have a strong background in bioinformatics or computational chemistry, experience in data analysis, and solid English-language skills. Programming experience is highly recommended. Candidates should demonstrate above-average interest in the research topic, self-motivation, ability to work independently, excellent team skills, and organizational aptitude. Applications must include a comprehensive CV, transcripts, and names of three potential references.

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