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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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strong publication record (first-author papers in high-impact journals preferred). Demonstrated expertise in at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual
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at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual cell, foundation models, graph neural networks, or multimodal omics integration). Epigenetics (DNA methylation
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Applications are invited for a Postdoctoral Research Associate in Machine Learning for Chemistry to work in the research group of Professor Volker Deringer at the Department of Chemistry. About the
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disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g., ethnography
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analyses. Machine learning for biological data (e.g., protein language models, transformers, generative models) and interest in building interpretable tools for experimental colleagues. Qualifications PhD
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and
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experience with distributed control, cyber-physical systems, smart transformers, machine learning, power systems or systems engineering. You have solid skills in modelling and simulation using software tools
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data management and machine learning is also preferred. An interest in energy system topics such as the green transition, sustainable energy systems, digital energetics etc. is preferred. Experience