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Postdoctoral Research Associate (f/m/d) for an Interdisciplinary Research Project on AI in Education
of communicative AI appropriation by students and teachers in secondary schools and how this is interwoven with the data infrastructures, design decisions, data models, and algorithms of AI platform providers and
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, voltage converter modules for electromobility, laser systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow’s technology in
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Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys ). The PhD position is focused on efficient algorithms for the simulation of non-adiabatic exciton transfer dynamics in light
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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exploration, optimization, and search algorithms in extremely complex and enormously large spaces motivated by physics and chemistry (RL, BO, Large-Scale Ansatze, …) AI-driven discovery of hardware for some of
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particular focus on the biosynthesis pathways of secondary plant metabolites (flavonoids). Your tasks will include: Applying controlled stress treatments Phenotyping stress responses with various sensors and
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processing Simulation and verification of the implemented algorithms with test vectors Integration of IP cores into an OFDM-based Physical Layer Debugging of implemented designs in a LiFi testbed Collaboration
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to develop automated algorithms for downscaling drivetrain components for specific test purposes. Furthermore, you will perform multiple case studies to analyze the performance of the developed scaling methods
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electrical sensors, polyurethanes, and biologically active extracellular vesicles. These solutions aim to prevent inflammation, promote tissue regeneration, and minimize infection-related complications such as
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or natural sciences Sound knowledge in machine learning algorithms, statistical methodologies, and biological network analysis Experience with the analysis and integration of transcriptomic and multiomics data