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, so that it can be easily used in practice (fast optimization, embedded decision-making, online updating). 1. Design a lightweight statistical/probabilistic surrogate model, integrating: • an estimation
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-level decision-making, it does not address the strategic optimization of fleet-wide renewal plans under uncertainty—a critical need for organizations aiming to decarbonize cost-effectively and in
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to optimize their durability and efficiency under industrial conditions. The goal is to contribute to a sustainable energy storage solution while avoiding the use of expensive metals. The postdoctoral
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(Postdoctoral Position) Availability: Immediate Required Level: PhD in Cell Biology, Biotechnology, Biochemistry, or a related field Main Responsibilities: We are seeking a motivated postdoctoral researcher to
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, CT, and other imaging techniques. Design and optimize multiparametric models to analyze complex imaging datasets and extract clinically relevant features. Develop and optimize newer clinically relevant
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optimization and Al tools to coordinate and optimize the role of ESS within the onboard microgrid. This project finds it context in the urgent need to reduce greenhouse gas émissions and improve the energy
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theoretical basis for modelling functional biodiversity, based on eco-evolutionary optimality (EEO) theory. The PDRA will be explicitly responsible for statistical analysis of plant trait data and the
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probes. The postdoc will play a key role in designing and optimizing imaging devices, integrating hardware and software, and collaborating with a multidisciplinary team of clinicians, engineers, and basic
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condensation-based system optimization. The positions are designed for early-career scientists with a strong background in thermal sciences, energy systems, or water technologies, and a demonstrated ability to
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an integrated model of plant carbon allocation, based on eco-evolutionary optimality theory. The PDRA will be explicitly responsible for designing an approach to evaluate and model carbon allocation to non