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maintaining systems and services, building scalable pipelines, optimizing performance, and ensuring high quality in both data and models. We are looking for individuals who are passionate about technology and
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device processing to optimize different important properties, such as high frequency operation, output power, linearity, and efficiency. The goal is to explore the limitations of III-nitride semiconductor
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the Climate Compatible Growth project, funded by the UKAID/FCDO. The ultimate goal of the effort is to deduce the potential for AI to aid in determining the most influential factors for (cost-) optimal
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are not limited to models and algorithms for knowledge discovery, novel algorithmic and statistical techniques for big data management, optimization for machine learning, analysis of information and social
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and enhance grid resilience. This project aims to develop optimal coordination and control strategies for microgrids to achieve self-balancing when they are disconnected from the grids, and grid support
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feedstocks. ACCELERATE gathers leading academics and industries that want join forces. Within this effort, this position will focus on the engineering, analysis, and optimization of catalytic reactors
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projects from low level hardware interfaces to high level optimized applications mainly in Python and under Linux Increasing the functionality and reliability of the beamlines in order to realize
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments
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computing, with a focus on performance analysis, development, and optimization of scientific simulation codes. The work involves applications in plasma physics, computational fluid dynamics, and molecular
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mathematics, such as extreme value theory, inference for stochastic processes, optimization theory, and/or Monte Carlo simulations. Experience in obtaining research grants in national and/or international