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Field
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learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model parameters that have been learned from data. For instance
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are offering a fully funded PhD position in the field of Physics-informed Learning-based Control. This interdisciplinary research area bridges control theory, machine learning, and physics-based modeling
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for Nuclear Research (NCBJ) is inviting applications for a position PhD student - scholarship (machine learning-driven modeling of metallic glasses) Location: Otwock - Świerk - in the outskirts of Warsaw with
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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available projects . Please indicate in your cover letter which of the following projects you're interested in: PhD 1: A collisional model for dust aggregates, based on continuum mechanics PhD 2: Dust
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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Join the Laan Lab at TU Delft to unravel the mesoscale physics of how cells maintain robustness through evolution using live-cell imaging and multiscale modelling. Job description Cells are often
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ERC Advanced Grant “De Tenebris” (PI: G. Bertone) and develop precision models of binary black holes in astrophysical and dark matter environments. Join Us! You will join the GRAPPA centre of excellence