173 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" PhD positions in Norway
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utilization and development of materials. The Department of Physics is one of eight departments in the Faculty of Natural Sciences . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294062
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for a PhD education Master students can apply, but the MSc degree must be obtained and documented by 1st of July 2025 You must meet the requirements for admission to the faculty's doctoral program (https
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of eight departments in the Faculty of Engineering. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294565/phd-candidate-in-cost-eff… Requirements Research FieldEngineeringEducation
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the health services. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290397/phd-candidate-in-medicine… Requirements Research FieldMedical sciencesEducation LevelMaster Degree
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therapeutics. For more details see this review: https://doi.org/10.1016/j.trecan.2022.09.001 Please get in touch if you don’t have access to the review. The candidate will: Perform Oxford Nanopore sequencing
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inventories and provision of environmental information. Similarly, the developments in AI and machine learning allow for new and improved processing of remotely sensed data supporting precision forestry
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find more information about the research group here: https://www.med.uio.no/klinmed/forskning/grupper/kardiovaskular-crg/ The PhD candidate will be funded by the K. G. Jebsen Centre for Cardiac
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interested in learning more Experience using process simulator AspenPlus or Hysys, and you have used them to simulate absorption processes Experience in fitting and validation of models Experience in
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research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research . Are you motivated to take a step towards a doctorate and open exciting career
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is internationally recognized, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference