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-winning team of PhD and master’s researchers advancing the next generation of energy efficiency and intelligent systems for industrial applications. Based within the School of Engineering and Architecture
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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the project team, you will ensure the simulation of drone missions using state-of-the-art tools for AI learning and demonstration. You will be responsible for producing training data for vision models and
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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Carolina 27705, United States of America [map ] Subject Areas: History / History , Oral History Art Education Teaching and Learning History of Art / History of Art Social Movements Appl Deadline: 2026/03
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this diversity. Our research spans comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced
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their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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of the ZTW under the supervision of the HAITrans research group leader Univ.-Prof. Dragoș Ciobanu, PhD. Your personal sphere of play: Your future position is within the HAITrans research group (https