PhD candidate in “Computational Modeling of Biomimetic Membranes” (f/m/d)

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.

• A Master’s degree in a relevant field, such as (theoretical) physics, biophysics, computational biology, chemistry, or a related discipline
• A strong interest in computational research at the interface of membrane biophysics, materials science, and synthetic biology
• Basic experience with molecular dynamics simulations and foundational knowledge of relevant biology, biotechnology, biophysics, or statistical mechanics; additional experience in biomolecular simulation or coarse-grained model development is an advantage
• Some familiarity with programming or scientific data analysis
• A basic understanding of the concepts behind generative machine learning and large language models, together with an openness to learning AI-assisted research tools
• A good command of written and spoken English and the ability to communicate and collaborate in an international environment; knowledge of German is welcome but not required

We offer:

• A cutting-edge PhD project in an internationally recognized group that is part of the DFG SCALE Cluster of Excellence (scale-frankfurt.org), the Frankfurt Institute for Advanced Studies and Goethe University Frankfurt
• An inspiring, inclusive, and international research environment with close exchange across disciplines
• Close scientific supervision, excellent high-performance computing infrastructure, and regular interaction with experimental collaborators
• A funded PhD position with a competitive salary (65% TV-H E13) and social benefits
• Excellent training and career development options (affiliation with the Goethe University Frankfurt and the graduate school GRADE-SCALEit)
• The opportunity to live in Frankfurt am Main, a vibrant cosmopolitan city in close proximity to the Taunus mountain range