The AI4Science Group (former Computational Molecular Biology - head: Frank Noé) is an interdisciplinary research unit active in the development of machine learning methods for the physical sciences. We have a strong profile in computational statistics, simulation and learning algorithms, and scientific software development. As a closely collaborating, international team of mathematicians, computer scientists, chemists and physicists, we put great emphasis on bridging the gaps between the various disciplines.
Our main research areas are: Physics-constrained learning algorithms, complex dynamical systems analysis, efficient generative learning methods for statistical mechanics, highly accurate machine learning methods for quantum mechanics and inference and enhancement of cutting-edge microscopy method.
 
Job description:
We are looking for a student assistant (m/f/d) for the development of deep learning methods for quantum chemistry calculations using quantum Monte Carlo. In addition, we would like support in the application for the calculation of large and highly accurate data sets of energy and electron density of molecules with strongly correlated quantum states.
 
Desirable:
- Enrolment at a German university.
- Major in physics, mathematics, computer science or related subject
- Programming experience in Python
- Experience with PyTorch or similar libraries for neural networks or interest in familiarizing
- Good knowledge of machine learning, especially deep learning methods or interest in familiarizing
- Good knowledge of quantum mechanics and its mathematical tools or interest in familiarizing
- Knowledge of Monte Carlo methods or interest in familiarizing
- Fluent in written and spoken English (B2)
- Gender and diversity competence
 
For further information, please contact Prof. Dr. Frank Noé (frank.noe@fu-berlin.de).