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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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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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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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, including finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks
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contribute to the activities including TES unit development, laboratory testing and techno-economic analysis to identify optimal integration opportunities. Cooperation with industrial and academic national and
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simulations to experiments in subatomic physics. The Plasma Theory group within the Division conducts research on acceleration and radiation generation in magnetic fusion, laser-produced and astrophysical
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topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the postdoc can be involved in
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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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the kinetics of enzymatic polymerization processes in biological environments. Expand and tailor enzyme repertoires to optimize functionality and electrode performance. Collaborate within a multidisciplinary and
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/ ) at the centra for molecular life sciences – SciLifeLab. The project takes place in collaboration with researchers at the centra with the goal of analyzing cellular processes on the nanoscale. Project aims and