196 parallel-computing-numerical-methods-"Simons-Foundation" positions at Technical University of Denmark
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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be applying methods such as sensitivity analysis, robust optimization, and stochastic modelling as you work on your project. You will be seconded with the Chalmers University of Technology (Sweden) and
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Job Description Are you worried about the coastal regions in an era of climate change and plastic pollution? Do you want to play a part in the development of a novel numerical model that can shed
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optimal alternatives that may be relevant for the decision maker. You will be responsible for developing new, fast solution methods for stochastic optimization problem that can find many near-optimal
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Job Description Would you like to become part of the solution toward green energy transition, by helping develop the methods for modeling future power and energy systems? The Renewable Plants in
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grasp of spatial statistical methods in R is considered highly advantageous. Excellent communication skills are required, with proficiency in English and preferably one of the Scandinavian languages
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phenotypic and genomic AMR surveillance, delivering training, and coordinating inter-laboratory testing and proficiency assessments. Research in the field of innovative AMR surveillance methods and laboratory
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for research and innovation in the area of food allergenicity prediction. Responsibilities and qualifications In this PhD project you will contribute to the development of innovative methods allowing