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, Machine Learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and Computer Graphics are especially encouraged to apply. The School has five divisions: Biological and Life
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advanced machine learning feature detection to enable evolving subsea scenes to be robustly aligned across repeat surveys. You will develop probabilistic models to detect subtle changes under noise and
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machine learning or chemometric algorithms, LDIR, Py-GCMS and Raman, Caco-2 cells Additional Information Eligibility criteria Mandatory: *PhD in science, chemistry, food engineering or related disciplines
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. For more information about the network, consult https://divine.unimi.it/ What are you going to do You will: be affiliated with the AISSR and participate in its organized PhD training. The academic work is to
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to validate the tools against practical design requirements. The successful Machine Learning Engineer will have the following skills, experience and attributes: MSc/MEng or PhD (desirable) in Machine Learning
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Classification Title: RES AST SCTST Classification Minimum Requirements: PhD in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Machine Learning or a closely related
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for probabilistic unsupervised learning for structured biological data. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/307053/3-years-phd-position-in-probabilistic-machine
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UNIVERSITE DE BOURGOGNE (University of Burgundy) | Le Creusot, Bourgogne | France | about 8 hours ago
active sensor in the control loop of complex robotic systems. This team conducts research on robust control, state estimation by vision, visual servoing and machine learning applied to cyber-physical
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across Duke and other institutions. Applicants should hold, or expect to complete before the start date, a PhD in computer science, machine learning, natural language processing, or a closely related field
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phase-field simulations. Experience in developing AI or machine learning models for physics-based scientific or engineering applications. Proficiency in Python, scientific computing and machine learning