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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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data. Building on these results and codebases, the successful candidate will work on a bioinformatics and machine learning research project on the inference of alternative splice forms using deep
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Pandemic Disease in Preindustrial Europe (1300–1800): Combining History, Machine Learning, and the Natural Sciences (EUROpest)”, funded by the European Research Council (ERC) as an ERC Synergy Grant
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coupled hydrological and groundwater modelling, combined with machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics
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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based