Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
-
Field
-
the genetic etiology and developing diagnostics and treatment methods for these diseases. Approaches range from human genetics, genomics, protein biochemistry and neuronal and glial cell biology to integrative
-
-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
-
? Then you might be the PhD candidate we are looking for! Join ANTICIPATE (Artificial Intelligence and Epidemic Modeling to Prepare Hospitals for the Next Respiratory Pathogen with Pandemic Potential), a
-
developed simulation models in open-source toolboxes such as OpenFAST. For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base.
-
developing the technologies that are needed to enable the large deployment of CO2 electrolyzers on the market. More specifically, you will devise strategies for mitigating salt precipitation via innovative
-
, and affords final target products in one step. Research challenges are to prevent undesired H2 evolution as a side reaction, and to achieve selective e-hydrogenation of substrates that tend to give
-
and shape a low-carbon economy and society. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ Candidates will be enrolled in the PhD program in Computer Science
-
. This programme, managed by the European Research Council (ERC) provides a distinctive funding mechanism devoted to scientific excellence for all scientific fields. The following types of grants are available
-
is to develop RL controllers that can learn from data while guaranteeing stable and safe operation in complex, nonlinear systems such as chemical plants and energy processes. By validating the approach
-
the preparation and defence of a PhD thesis focusing on the analysis of extreme events using deep learning methods. Your responsibilities will include developing deep learning-based methods for modeling extreme