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and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational research, research strategies and development, as well as education on both undergraduate and
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characterization of algal food protein ingredients, ensuring high yield and quality. The latter will be optimized from several aspects, including e.g., in vitro nutrient digestibility and volatile compound profile
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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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and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational research, research strategies and development, as well as education on both undergraduate and
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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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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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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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the use of crystallographic software and data processing pipelines Experience working with computation clusters and managing large datasets Proven ability to develop, maintain, and optimize scientific
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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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is expected that they will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and, after a training period, independently analyze genomic data using