Research Assistant (E13, Machine Learning, Agility Project, IV-354/24)

Research assistant - salary grade E 13 TV-L Berliner Hochschulen - for qualification

The Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin (Prof. Klaus Robert Müller) is seeking a Research Associate in Machine Learning for an Agility subproject. The agility project will be carried out in the research groups "Machine Learning for Molecular Simulation in Quantum Chemistry” led by Dr. Stefan Chmiela and "Probabilistic modeling and inference" led by Dr. Shinichi Nakajima.

Dr. Chmiela’s team is engaged in the modeling of multi-body systems with applications in quantum chemistry, particularly for predicting solutions to the Schrödinger equation. The overarching goal of the team is the development of models to accelerate accurate molecular dynamics simulations for the calculation of dynamic and thermodynamic observables of physical systems.

Tasks
Independent and responsible research in the field of machine learning. The goal of the advertised project is the development of new explanation methods (Explainable Artificial Intelligence, XAI) for atomistic modeling in quantum chemistry. The focus is on acquiring physically grounded insights to guide hypotheses in quantum chemistry. The associated tasks are:

• Development and implementation of XAI methods for ML models in quantum chemistry
• Incorporation of physical knowledge about the target systems into the models, e.g., distinguishing different kinds of short- and long-range interactions between atoms
• Evaluation of the developed methods using benchmark problems and contextualizing observations within physical theory
• Communication of results through presentations

Employer: TU Berlin / BIFOLD
Salary grade: TV-L E13 Berliner Hochschulen
Starting date (earliest): Earliest possible / for 3 years
Closing date: November 7, 2024
Full job posting: IV-354/24