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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep
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settings. Very good self organization. Desirable Skills Very good knowledge of fluid–structure interaction (FSI). Good experience with digital twins, model updating, or structural dynamics. Understanding
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related field from a recognised university. Knowledge and experience in modelling and simulation of microgrids or power systems using ETAP and/or MATLAB/Simulink. Experience in distributed energy resources
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evaluation Knowledge of numerical simulation, for example with land surface or hydrological models Genuine interest in data science and earth sciences Good organizational skills and ability to work both
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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systemsEducation LevelPhD or equivalent Skills/Qualifications Required skills, knowledge, and experience: Expertise in modeling and simulation (BPMN, DEVS, RO languages). Experience in the field of reconfigurable
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student in areas related to Computer Science. Basic experience in health data analysis. Python programming. Knowledge of machine models and deep learning. Intermediate English level. Specific Requirements
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to push the frontiers of multiphase reactor modeling and accelerate the scale-up of emerging net-zero technologies? Join us at the Department of Chemistry and Chemical Engineering ! About us Our
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation