PhD positions in deep learning based de novo protein design

Milles lab at the LMU Munich Gene Center and MPI of Biochemistry Martinsried

https://www.biochem.mpg.de/milles

De novo protein design has experienced a machine learning-fueled revolution, vastly expanding our ability to design complex and functional proteins beyond those found in nature. Our research group works at the intersection of de novo protein design, deep learning and fundamental biophysics of protein function, doing both computational design and wet lab biophysical characterization. 

We aim to deconstruct biological function by reconstructing such function de novo. Using deep learning-based protein design, we construct proteins free from evolutionary constraints that incorporate desired functions to better understand their underlying biological mechanism. Among other areas, we are interested in mechanisms at the host-pathogen interface: 

Project 1: Creating synthetic “harpoons”that can covalently target selected epitopes by reconstructing an autocatalytic mechanism from gram-positive pathogens, a potential tool for irreversible, covalent opsonization. 

Project 2: Designing self-strengthening catch-bonds, counterintuitive protein-protein interactions that bind more tightly under mechanical stress. These de novo catch bonds will be minimal models to build an understanding of their mechanism and could become the basis for novel biomaterials. 

We leverage our recently developed medium/high throughput screening technology to test designs (96-192 proteins per day), including biophysical characterization and AFM-based single-molecule folding studies. Thus, we can rapidly take an idea, transform it into protein design on the computer and finally validate it in the wet lab. Come join us to explore and push the boundaries of the de novo protein design space.

We are an interdisciplinary group, welcoming applicants with backgrounds in biology, physics, (bio-)chemistry, engineering or computer sciences. Candidates will perform both computational and wet lab work during their PhD.

Application via the Graduate School Quantitative and Molecular Biosciences Munich (QMB):

As part of QMB, you will additionally have ample opportunities for scientific exchange with world-leading scientists of various fields and develop your scientific career with lasting benefits. The international PhD training program at QMB emphasizes communication and collaboration across traditionally separate disciplines, including biochemistry, medicine, bioinformatics, experimental and theoretical biophysics, and applied mathematics.

QMB places a strong emphasis on experimental work while also encouraging students to engage in theoretical approaches to derive meaningful insights from their data. This dual focus on advanced quantitative experimentation and theoretical analysis, combined with the excellence of its participating scientists, positions QMB uniquely within the European scientific landscape.

Please note: All applications have to be submitted in English through our online application tool. Applications submitted by mail or email will not be considered.

For detailed information about our application requirements see: https://qbm.genzentrum.lmu.de/application/requirements/ 

In your application, you can select up to two research groups you are interested in. For details about research areas and participating research groups, please see: https://qbm.genzentrum.lmu.de/research/research-areas-groups/