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of autonomous flow reactors for chemical synthesis. The project aims at 1/ developing a new optimization Bayesian algorithm and 2/ improving the process-control software already developed in the team
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on creating and optimizing state-of-charge (SOC) and state-of-health (SOH) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities
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, cold chain logistics, and sustainable packaging systems, addressing critical challenges in product protection, supply chain optimization, and distribution system efficiency. We seek a highly motivated
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approach combining: • The implementation and optimization of environmentally friendly extraction processes, • A fundamental understanding of the associated inhibition mechanisms, and • Life-cycle analysis
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dimension of uncertainty in power system operations, necessitating more complex and adaptive decision-making processes for system operators. While some prototypical power system optimization problems have
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material quality. The resulting models will act as a predictive tool for process optimization and design improvements, providing a foundation for scalable industrial applications. Job Description: The
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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planning and operations, and the interaction with other infrastructures. Some of these tools will require the development of underlying optimization methodologies and analytics frameworks. The successful
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computationally efficient at simulating permanent magnet structures, and capable of leading to the globally optimal solution of the underlying design optimization problem. We aim to combine gradient-based
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expertise in plant sciences, optical technologies, and data processing. The existing imaging Mueller polarimeter, which is sensitive to the microstructural properties of biological tissues, will serve as the