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- ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação
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Web of Science in the required fields of knowledge; c) Have experience in the development of optimization models and methods, as well as their implementation and testing. 5. Formalization
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specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification
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are looking for a postdoctoral researcher in computational methods for aeroacoustics and optimisaiton related to wind turbines. The successful candidates will join the dynamic research team of Prof. Esteban
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to technologies optimization. The research team has the ambition to address all the needed scientific fields to understand turbulent and multiphase flows from simulation: numerical methods, turbulence models
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results, numerical modelling, and analytical approaches to support the development of respective reliable and efficient design concepts. Led by Prof. Christoph Odenbreit, the ArcelorMittal Chair of Steel
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ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação | Portugal | 2 months ago
: planning and execution of oceanographic campaigns; collection, processing, quality control and analysis of oceanographic and atmospheric data; numerical modelling with COAWST and associated tools
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
computational modelling and simulation in engineering, including numerical methods, finite element analysis, constitutive models, response prediction, or digital twins (0–4 points); Experience in computational
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is the development of hybrid models that combine our integrated national model of Denmark with AI-based methods to improve predictions of floods and droughts. We seek to enhance our ability to predict
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-tuning, or related optimization methods. Experience with cloud infrastructure, MLOps or LLMOps, containerization, or production deployment. Frontend and/or backend development skills. We offer ETH Zurich
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relevant to physics, such as CNNs for image-based field prediction, Graph Neural Networks (GNNs), or Physics-Informed Neural Networks (PINNs) Solid grasp of numerical methods, partial differential equations