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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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, Duke University Biology Department to study how archaeal microbial communities respond to stress in hypersaline environments. A PhD in computational and/or experimental biology is required in fields
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physics. Participation in detector research and development, especially for low-latency event selection in trigger systems. Development of new artificial-intelligence and machine-learning techniques
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging
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) Corrosion behavior (electrochemistry & high-temperature oxidation) In-situ monitoring of AM processes Computational skills in: Phase-field modeling, Machine Learning, FEM, DEM, COMSOL Alloy design (CALPHAD
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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) Development of an Augmented Smart Classroom for Personalized Learning (SmartClass) serving as a test-bed for the collection and analysis of students and professors data, leveraging on data analytics and machine
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physics. Development of new artificial-intelligence and machine-learning techniques for high-energy and nuclear physics. Close interaction with our collaborators in the EIC and the BNL theory group will be