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yield and quality. The latter will be optimized from several aspects, including e.g., in vitro nutrient digestibility and volatile compound profile. The work will be carried out in close collaboration
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are looking for a curious and driven postdoctoral researcher to join a project focused on improving how we study and optimize medical treatments. The work centers on advancing a vessel-on-a-chip platform—a
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments
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. The postdoctoral project will be focused on the design of optimized generation schemes for tailor-made electron beam and radiation sources in laser-produced plasmas. As a postdoctoral scientist, you are employed by
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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is meritorious for future research duties within academia as well as industry/the public sector. The postdoctoral project will be focused on the design of optimized generation schemes for tailor-made
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division of the Department of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and
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, design and characterization of quantum processors Development and optimization of nano-fabrication processes for large-scale devices Development of optimal control techniches to achieve fast and high
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano