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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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Assistant Professor in Marine Biology & Ecology - Biomedical Science or Quantitative Systems Ecology
ecologist working in coastal systems, who applies modern approaches in causal inference, experimental ecology, spatial modelling, and data science, including the use of machine learning to produce rigorous
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, single-unit recordings. 2. Strong background in computation modelling of behavioral or neural data. 3. Proven experience with statistics, machine learning and/or brain stimulation. 4. Proven experience
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Brest, Bretagne | France | about 20 hours ago
ecosystems under natural and anthropogenic pressures. In this field, the unit carries out research and provides expert analysis aimed at understanding, modelling and predicting the spatial and temporal
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marketing strategy, supply chain and logistics, digital distribution, and operations research. Leveraging the latest technologies, such as artificial intelligence, machine learning, and large language models
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, or R&D environment. Experience developing CAD models and generating CAM toolpaths for CNC machining of metals and plastics. Experience performing assembly and testing of experimental equipment
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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and develop complex, custom Artificial Intelligence models and applications. This role incorporates Machine Learning, Deep Learning, Computer Vision, Large Language Models, and Agentic AI technologies
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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and non-traditional technology providers. As national security priorities, acquisition models, and innovation cycles evolve, SEI must continue to adapt its posture, pace, and external engagement while