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, Mathematical Engineering, Mechanical Engineering or similar. Relevant skills: Strong background in machine learning/data science. Deep knowledge of neural network architectures (as a plus: PINNs, neural
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manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods and model-based approaches to design and evaluate resilient reconfigurable
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within our BSc. and MSc. program by contributing with teaching and supervision? Then the Department of...
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research in peer-reviewed journals and presenting at international conferences We are looking for a candidate with: A PhD in oceanography, climate science, applied mathematics, computational science, or a
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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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. DTU Compute DTU Compute – Department of Applied Mathematics and Computer Science – is an internationally unique academic environment with 400 employees and 10 research sections spanning the scientific
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inaccuracy, irregular sampling grids, variations in measurement conditions, and other measurement uncertainties. The successful candidates should have excellent grades, strong mathematical and simulation
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members working on novel high-resolution microscopy techniques to experimentally quantify transition probabilities, alongside density functional theory (DFT) calculations of defects in feldspar. This inter
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theory Competency in processing and analyzing time-resolved data and handling large datasets. Synthesis and characterization of polyoxometalates Electrochemical catalysis and characterization techniques
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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