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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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industry to a great extent. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the postdocs will be positioned to the section
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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program aimed at tackling one of the life science industry’s biggest challenges: Closed-Loop Design and Optimization of Biologics. The research program will build on the recent advances in protein design
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part of the Dynamical Systems Section. We perform research within a broad range of areas within dynamical systems including modeling, optimization, forecasting, and controlling in both deterministic and
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to enhance enzyme stability, recyclability, and catalytic efficiency, including advanced surface modifications, optimized support materials, and improved reactor designs. The Department of Chemical and
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translate fundamental insights in membrane technology into practical, impactful solutions. Responsibilities and qualifications Develop and optimize highly structured membranes for membrane distillation. Lead
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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carriers within defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and
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for Surface enhanced Raman Scattering (SERS). You will spearhead and coordinate our development and optimization of new SERS substrates as well as sample preparation of clinical samples that we receive from our