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: PhD in computer science, machine learning, operations research, transportation engineering or a related field. Programming skills in C/C++ and Python, along with experience working with simulation
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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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for analysis and dynamic configuration. Publish results in high-impact venues. Collaborate with academic and industrial partners in Shift2SDV. Co-supervise MSc and PhD students. Optionally contribute to teaching
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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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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
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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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CO2 capture from the atmosphere. Your objectives will include to: Develop new optimization and/or machine-learning based reconstruction and segmentation algorithms to improve image quality in time