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research unit of CNRS, Grenoble INP, and Université Grenoble Alpes, is a center of excellence in materials science and innovative processes. It spans diverse fields—from metallurgy to nanomaterials and
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, international group of 13 researchers from 8 countries, with expertise across energy systems and markets, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the
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encompasses model compression and optimization for edge deployment on UAV-mounted processors to support real-time inference. The candidate will collaborate with industrial partners for real-world data
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an emphasis on reaction development and optimization. Training BioProcess aims to train the next generation of bio-innovators. Our interdisciplinary programmes prepare PhD students and researchers with the real
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, sustainable multi-salt electrolyte formulations will be developed and optimized for compatibility with hard carbon anodes, with the aim of enabling safe operation, fast charging, and long cycle life. We offer
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signal processing methods and a modelling environment, aided by unique hardware-in-the loop, to assess the detection and estimation algorithm performance and determine optimal multistatic configurations
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chemical production, the focus is on optimizing yield, distribution, or conversion by testing different operating conditions (pressure, concentration, temperature, etc.) and at isothermal conditions. Then
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and how these intersect, their labour cost rates will be calculated. These calculations, based on optimal socio-economic work patterns, and on pre-industrial agricultural subsistence activities, will
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project, you will help design, simulate, and optimize these next-generation communities — making clean, local, and intelligent energy systems a practical reality. Your key responsibilities include
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3.5-year D.Phil. studentship Project: Optimization for real-time electricity grid operations Supervisor: Jack Umenberger This project concerns real-time balancing of energy in the electricity grid