Jobbörse
Veröffentlicht am 16. Okt. 2026
Frankfurt Institute for Advanced Studies (FIAS)
60438 Frankfurt am Main
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Gehalt (Schätzung)
Grobe Schätzung: 44.000 €–58.000 €/Jahr
Introduction
The Frankfurt Institute for Advanced Studies (FIAS) is looking for a PhD candidate in “Computational Modeling of Biomimetic Membranes” (f/m/d)
The Frankfurt Institute for Advanced Studies (FIAS) is a hub for theoretical and computational research dedicated to solving complex scientific challenges. We pioneer an interdisciplinary approach, leveraging advanced theoretical methods in the natural and life sciences and computational methods to model complex self-organizing systems of nature.
At the dawn of exascale computing and artificial intelligence, computational life sciences are entering a new era. Simulations of subcellular architectures and small cells at molecular-level resolution are becoming a reality and will allow unprecedented insights into the biology of living systems. Yet connecting molecular structure to function within these large-scale simulations remains a major challenge. The newly established Virtual Integrative Platforms for Synthetic Biology (VIPSynBio) group at FIAS addresses this challenge by working toward the computational engineering of minimal biomimetic systems that reproduce selected biological function, drawing on concepts and design principles from synthetic biology.
We’re looking for a motivated PhD student to join us in this new research direction.
Your PhD project focuses on understanding and engineering biomimetic membranes through computational methods. You will uncover how membrane structure and composition affect the stability, function, and regulation of membrane proteins. Working closely with experimental collaborators, you will use these insights to generate testable predictions for novel membrane compositions and protein variants relevant tonanotechnology , building on our recent work on lipid-polymer hybrid membranes. Furthermore, you will combine molecular simulations with AI-enabled agentic workflows to identify broader biophysical principles of membrane-protein regulation and guide experimental design within the SCALE Cluster of Excellence . Overall, this PhD project combines fundamental membrane biophysics with predictive design, aiming to deliver both new mechanistic insight and rational design principles for custom biomimetic membranes.
In your research, you will use high-performance computing , multiscale molecular simulations, and machine learning together with AI-assisted agentic workflows to address research questions at the interface of biology, nanotechnology, and materials science. Coarse-grained Martini simulations will be a central method, and the VIPSynBio group is one of its core developers. Depending on your interests and strengths, you can develop a focus in computational membrane biology, coarse-grained model development, or AI-enabled scientific workflows. The project is embedded in an international network and in close collaboration with experimental groups within and beyond SCALE, with opportunities for research visits, interdisciplinary training, and presenting your work at international conferences.
The position is based in the VIPSynBio group, led by Dr. Fabian Grünewald at the Frankfurt Institute for Advanced Studies (FIAS) and the Goethe University Frankfurt.
Applications may be submitted until 5th October 2026 . Ideally, the successful candidate will start in December 2026 . The FIAS and the Grünewald group aim to offer a diverse and inclusive working environment and explicitly encourage applications from people belonging to underrepresented groups in science.
Contact
Please upload all documents as a single pdf file via our online portal at:
https://jobapplication.hrworks.de/?companyId=amb4af72&id=8c5fc4
Scientific questions: Dr. Fabian Grünewald (gruenewald_at_fias.uni-frankfurt.de) Administrative questions: Meike Taplik (hr_at_fias.uni-frankfurt.de)
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Vollzeit-Referenzwert: 37.000 €–58.000 €/Jahr
DocMorris AGBerlin
Glassdoor 3,4 (40)
Grobe Schätzung: 44.000 €–58.000 €/Jahr
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Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung
Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung