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Université de Technologie de Belfort-Montbéliard | Belfort, Franche Comte | France | about 20 hours ago
(formulation, algorithms, applications in structural mechanics), HPC computing, reduced-order modelling, machine learning, Vibrations and structural dynamics, architected materials, Additive manufacturing
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single micro-sphere of frozen water. This bulkiness presents a significant limitation, and the emission has no directional control. This PhD thesis will build on a decade of research into novel laser
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techniques for data storage/retrieval/processing/visualization on large scale. Cybersecurity Software engineering Machine/deep learning Technical aspects of human computer interaction (HRI, multi-modal
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of and experience with hydrological and/or hydrogeological modeling - Knowledge of and experience with AI concepts (machine learning, deep learning, and PINNS) and/or digital twin development - Experience
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to candidates from a broad range of AI subfields, including, but not limited to machine learning, generative AI, computer vision, representation and reasoning, natural language processing
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computational modeling and/or analysis of complex biological systems, integrating state of the art tools such as machine and deep learning approaches. Experience in managing biological databases and statistical
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clinical research center is a plus; Knowledge and experience of machine learning methods; Constructive attitude, flexibility, outgoing and service oriented; Excellent communication, negociation and
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required. • Programming skills are required. • Knowledge of Natural Language Processing and Machine Learning is preferred. • Fluent English required, both oral and written. French is appreciated but
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Context and Motivation Bilevel optimization problems, in which one optimization problem is nested within another, arise in a wide range of machine learning settings. Typical examples include
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Keywords: theoretical biophysics, machine learning, kinematics, (structural) biology. Context. Machine learning techniques have made significant progress in prediction of favourable structures from