
Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Hessian scientists of various disciplines are using High Performance Computers for their research.
Displaying 1 - 30 of 69
Bayesian observer and actor models have provided normative explanations for many behavioral phenomena in perception ...
Hydrogen has emerged as a crucial element in the pursuit of decarbonization and the transition to a sustainable energy ...
The rapid development of robotics has enabled legged robots capable of performing highly dynamic tasks such as walking ...
The industrial production of high-density polyethylene (HDPE) through the catalytic polymerization of ethene is an ...
The polymerization of low-density polyethylene takes place at high temperatures and pressures up to 3000 bar. Under ...
The project seeks to create a comprehensive model linking nanoscale phenomena to larger-scale behaviors to better ...
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
In the research area of circular building design, design concepts for sustainable masonry are being implemented using ...
Germany has the ambitious goal of covering all electricity generation by renewable sources by 2045. The Kopernikus ...
Laser powder bed fusion (LPBF) is an additive manufacturing technology involving a gradual build-on of layers to form a ...
Layered transition metal oxides, derived from the model system LiCoO2, are used as cathode materials in Li-ion batteries ...
This work aimed to apply deep learning, specifically Mamba, to the problem of codon optimisation in order to be able to ...
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
The application of metallic glasses (MGs) is limited by their brittle behavior at room temperature [1]. In order to ...
A jet engine’s high-pressure turbine, which is located downstream of the combustor, is subject to an extremely high ...
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
Optoelectronic materials have attracted significant attention owing to the global energy shortage and environmental ...
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
To understand and study complex materials at the atomic level, it is essential to be able to calculate forces and ...
The low-density polyethylene polymerization process takes place at high pressure and temperatures. Knowledge of the ...
The simulation of materials on the atomistic scale requires a description of interatomic interactions. Quantum ...
The project was majorly dedicated to build cell mechanistic models and study cell mechanics and cell migration. Both ...
The project aims to develop a bridging model that connects the nanoscale to the upscaled levels for understanding the ...
Active matter consisting of motile agents such as bacteria, algae, or synthetic microswimmers on the microscale and ...
Recent work has shown that deep neural networks are able to predict human similarity judgments with high accuracy (e.g ...
Structural engineering, particularly concrete systems, has long focused on understanding the distribution of internal ...
Coarse-grained molecular dynamics (MD) simulation provides a faster alternative to all-atom MD simulation, essential for ...