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Field
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spatiotemporal decompositions of large high-resolution simulation datasets. • Develop and train machine learning architectures using reduced-order predictions together with heterogeneous observational data
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focuses on detecting underwater acoustics using AI methodologies. Additionally, CFD simulations combined with physics-informed machine learning will also be examined. Several research and industrial
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for combining experimental, simulation and theoretical methods. The PhD Research Fellowship will exist in an innovative environment with the possibility for collaboration with a range of academic and development
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"How to apply", otherwise your application will not be evaluated. We will also emphasize motivation and personal suitability for the position. We are looking for someone with good social and
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and targeted, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across
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, and other qualifying activities. Career breaks, including parental leave, that are noted in the CV will be taken into consideration when evaluating applicants’ academic record. Copy of Master’s thesis
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order to be considered as an applicant in these groups, the applicants must meet certain requirements. You can read more on this here: https://arbeidsgiver.difi.no/positivsaerbehandling . We encourage
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for an interview. In order to be considered as an applicant in these groups, the applicants must meet certain requirements. You can read more on this here: https://arbeidsgiver.difi.no/positivsaerbehandling . We
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and Sustainability (CREDS ), part of Inland School of Business and Social Sciences, University of Inland Norway (INN), invites candidates to apply for a three-year PhD research fellowship. The position
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-informed ML surrogates for efficient simulation ML-supported optimization of HPC software Jarli & Jordan/ UiO via Unsplash Jarli & Jordan/ UiO What skills are important in this role? The Faculty