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Field
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field of research Participate in education, and PhD and master student supervision Profile Strong background in computational biology, bioinformatics, machine learning, or a related quantitative field
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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reinforcement learning. The project will investigate a simulation platform that reproduces the structure of real prospection activities by integrating multiple, heterogeneous geospatial and archaeological data
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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computing, high-performance computing (HPC), or machine learning (ML) Interest in Standard Model measurements and/or searches for new phenomena Application Review Review of applications will begin once the
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (www.foylab.xyz/) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving
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research in the natural, mathematical and computer sciences with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and
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intelligence / machine learning, biostatistics, computational biology, or related subject area A track record of previous publications in bioinformatics analysis of large-scale biomedical data, e.g.: omics
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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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Generation, digital double, human-like avatars. Profile PhD in Computer Vision Background in CS Research experience in gen AI, deep learning Strong computational and analytical skills, as well as experience