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groundbreaking research. The project is devoted to learning-based control for high-dimensional data. Application to individually optimized immunotherapy for cancer will also be considered. The grant covers two
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Council (VR). The project is centered around inverse optimal control/inverse reinforcement learning, both for continuous-time and discrete-time systems. In particular, we are looking for a strong candidate
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: Metallurgy, Process physics modelling, and Process development and control. Our main aim is to fundamentally study and improve our understanding of welding and welding-based additive manufacturing processes
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-group strategies, stereochemical control, and structural optimization, thereby offering both challenge and creative freedom. Downstream, the monomers will be incorporated into PNA/γPNA oligomers
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carbon support material from hardwood biomass through a controlled pyrolysis process. The biochar obtained from the pyrolysis process will be subjected to chemical activation with KOH/H2O2 and H3PO4
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optimization of the advanced spectromicroscopy systems at the MAXPEEM beamline. Provide high-level experimental support and technical guidance to international visiting researchers (beamtime users). Research
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prototype different thermal technologies and evaluate as well their integration and control within given hybrid systems, and under different market scenarios and industrial applications. Among
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development, maintenance, and optimization of the advanced spectromicroscopy systems at the MAXPEEM beamline. Provide high-level experimental support and technical guidance to international visiting researchers
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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maximal signal-to-noise and detection of picomolar levels of protein in the blood. The laboratory’s part of the project is to test and optimize this new strategy and subsequently use it to evaluate