Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this project, we highly
-
/technical challenges Project FITNESS will build upon and extend state-of-the-art methods [1], [2] recently developed within the team, showing to outperform existing, machine-learning based approaches in
-
defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
-
technologies to enhance vehicle performance and safety, including the creation of generalised machine learning training processes. Additionally, AI-driven adaptation strategies will be investigated to enable
-
The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
-
that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method
-
achieved through a variety of optimization, machine learning or AI-based heuristics. Optimization of revenue stacking models for hydrogen assets that have to supply a number of market-based services
-
thematic areas: Control systems, computational intelligence and machine learning, autonomous systems, optimization and networks, embedded and real-time systems hardware and software, fault diagnosis, cyber
-
PhD candidate in the automated detection of measurable residual disease in hematological malignancie
(deep learning, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Strong interpersonal skills Ability to work
-
calculations of well-characterized 2D materials, simulations of electron microscopy images, and machine learning methods to reconstruct the 3D atomic positions of materials from a 2D microscopy image. The