The Clementi group in the Physics Department at Freie Universität Berlin offers a MSCA Doctoral Fellowship to work on the development and application of coarse-graining methodologies to study macromolecular dynamics with machine learning and experimental data, integrative structural biology, and membrane protein modeling.
Our group works on the definition and implementation of strategies to study complex biophysical processes on long timescales.
We use data-driven methods for systematic coarse-graining of macromolecular systems, to bridge molecular and cellular scales.
We work on a theoretical formulation to exploit the complementary information that can be obtained in simulation and experiment, to combine the approximate but high-resolution structural and dynamical information from computational models with the "exact" but lower resolution information available from experiments.
The position will be part of the project TRACK THE TWIN, a joint research project funded by EU. It is limited to the 30.11.2028.

Job description:
- Application of specially developed approaches to define for transferable force-fields with machine learning for different classes of complex molecular systems (proteins and materials) and different resolutions.
- Use of the developed force-fields to simulate specific molecular systems in collaboration with experimental groups, to address questions of biomedical or industrial relevance.

The candidate will develop and use machine learning methods (mainly graph neural network   architectures) to design representations and transferable energy models for proteins and materials.

Requirements:
Candidates must have a Master in Physics, Chemistry, Applied Mathematics, or related fields.

MSCA Doctoral Candidate Allowances: The gross monthly allowance will be either 3.942,20 EUR or 4.602,20 EUR depending
on the family status.

Desirable:
Fluent English, spoken and written
Strong background in statistical physics
Previous experience in machine learning, especially deep neural networks
Previous experience with molecular simulations