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decision-making and research findings. Qualifications & Competencies: Minimally a PhD degree in Artificial Intelligence, Computer Science, Optimization, or a related field. Strong foundation in multi-agent
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and development in the chemical conversion and valorization of hazardous waste streams, focusing on complex, reactive materials. Involves process design, optimization, and scale-up, including reaction
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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Responsibilities: Finance: Keep track of expenditure and remaining budget in an organized manner, ensure that the spend is optimized and on track with respect to goals set for the grant; prepare financial and
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development, validation, and optimization of 3D-printed propellers. This includes conducting hydrodynamic analysis, finite element modeling, as well as overseeing site-based test bedding, data collection, and
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/or Typhoon HIL and conduct real time simulation studies/experimentation. Design and develop an intelligent and optimal energy management system (EMS) controller for the optimal operation and
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. The design and integration of CHIPLETS is a complex multi-physics task that requires substantial design space exploration and co-design and co-optimization accounting for the electrical, thermal and mechanical
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) to identify delirium risk factors and optimize prevention strategies. Maintain and optimize databases for high-volume data storage, integration, and retrieval. Collaborate with data engineers to design
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to collaborate with scientific teams at CEA, France. Key Responsibilities: Investigate how plasma shaping influences turbulence in tokamaks, with the goal of understanding and optimizing its role in enhancing
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Responsibilities: The successful applicant will be responsible for the development of Performing literature review and background study on collaborative AI Apply knowledge on foundation models to optimize training