78 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"IMEDEA-CSIC-UIB" positions in France
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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep
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should have a graduate degree (Master 2 degree). Him/her scholar background should include: • statistical/machine learning, statistical inference, clustering, classification • deep learning, variational
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within the project AI4TECSWriting a doctoral dissertation in computer sciencePublishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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strong background in optimization and machine learning. Good coding skills in Python, PyTorch are welcomed. Application Applications should contain a CV, a motivation letter, the grade records of the last
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, biology, computer science or related disciplines Strong computational skills, including machine learning, e.g. demonstrable project in a relevant field A strong first-author publication record in a relevant
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department, e.g. seminars, workshops and schools organised by the members
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Package 6), equipping them with advanced skills in reservoir modeling, machine learning, advanced oxidation processes (AOP), and microbial enhanced recovery. DCs will also develop intuitive fluid chemistry
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. The objective of this postdoctoral project is to develop a unified, AI-compatible framework for non-neural behavior based on dynamical systems and learning. Behaviors will be modeled as low-dimensional dynamical
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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