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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
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. Responsibilities and qualifications Qualifications: PhD degree in Engineering, Physics, Computer Science, or Applied Mathematics. Proficiency in scientific programming with Python. Excellent oral and written
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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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development, particularly in LabVIEW and C++ programming for high-precision measurement systems. As a key member of our team, you will lead the development and optimization of our high-speed dermal atomic force
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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. We are building up capabilities in technology and policy impact assessment building onto our existing optimization models and tools with the aim of developing a comprehensive understanding for whole
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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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focused on applying quantitative tools (e.g., statistics, machine learning, optimization, simulation) to healthcare delivery, healthcare operations and healthcare management as well as medical decision