A deep unsupervised Model for Protein Design
The design of new functional proteins can tackle many of the problems humankind is facing today but so far has proven very challenging1. Analogies between protein sequences and human languages have been long noted and a summary of their most prominent similarities is described. Given the tremendous success of Natural Language Processing (NLP) methods in recent years, its application to protein research opens a fresh perspective, shifting from the current energy-function centered paradigm to an unsupervised learning approach based entirely on sequences. To explore this opportunity further we have pre-trained a generative language model on the entire protein sequence space. We find that our language model, ProtGPT2, effectively speaks the
Strong-field Response of complex Systems
The interaction of light with matter covers a large number of physical phenomena that we literally see in our everyday life. Early scientists mostly focused on investigations of electromagnetic radiation in the visible range and at low intensities, where material polarization responds linearly to incident electromagnetic fields. Utilizing the compute clusters at PC2, this project aims at simulating and interpreting the strong-field dynamics of real molecules and larger systems in a rigorous real-space real-time approach including non-linear strong-field effects such as photoionization and high-order harmonic generation of systems ranging from small (chiral) molecules over nano-systems to the condensed phase.
Thermal Evolution and Dynamics of the Interior of Planets and Moons
Over the past decades, large-scale computer simulations have grown to become one of the most powerful approaches to study the interior of Earth-like planets. Geodynamical models are used to investigate the evolution and distribution of the temperature inside the planet that ultimately affects its structure and the way the planet cools over time. Combined with data obtained from planetary missions and laboratory experiments, these models help us to improve our understanding of the history and current state of planets in our Solar System and beyond. These models can teach us about the formation and evolution of planetary environments
CFD Simulations Ecurie Aix
Every year we, as the Formula Student Team of RWTH Aachen University, develop a completely new electric race car and revise a previous car to be able to drive autonomously. For our Aerodynamics team, the electric vehicle is the main focus. We try to find the best geometries for our car within the regulatory constraints and while keeping performance compromises with other design areas in mind.