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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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of the world’s largest research environments in computational science, with large activities in areas such as machine learning, optimization, scientific software development and high-performance computing
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from molecular dynamics simulation trajectories in silico. On the wet-lab side, the position involves generating both fluorescence and mass spectrometry data and optimizing protocols for its analysis
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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models. The project
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– protein interactions or enzyme optimization. Main responsibilities The candidate will use and develop methods within one, or multiple, of the following categories: Optical engineering, fluorescence
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical