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 ELEGANCE, a joint research project funded by EU. The fellowship is limited to a duration of 36 month. The monthly payment will be a lump sum in the range of 3.,00 EUR to 4.,00 EUR (gross salary before taxes, insurance, etc.) depending on your family status. For questions or further information feel free to contact us.
Job description:
- Application of specially developed approaches to define transferable force-fields with machine learning for different classes of complex molecular systems (proteins and materials) and different resolutions
- Interpretation and regularization of machine learned force-fields architectures
- 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 or comparable degrees
MSCA Doctoral Networks require that applicants must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting organisation for more than 12 months in the 36 months immediately before their recruitment date.
Desirable:
- previous experience in machine learning, especially deep neural networks
- previous experience with molecular simulations
- fluent English, spoken and written
- strong background in statistical physics