137 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD positions in Norway
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- NTNU - Norwegian University of Science and Technology
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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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of Natural Sciences . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290104/phd-position-in-theoretic… Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent
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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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the research fields of cardiovascular biomarker research and cardio-oncology. You can find more information about the research group here: https://www.med.uio.no/klinmed/forskning/grupper/kardiovaskular-crg
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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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collaborative EU funded doctoral training network HEALENAE: Health and Environment in Africa and Europe. The network will consist of 15 PhDs, that together will work and learn as an international cohort and
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department
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information can be found here: https://www.ntnu.edu/mai Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above
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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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Assessment of Cardiac Function and Outcome Prediction using Artificial Intelligence and Echocardiography". The project aims to develop novel AI models based on self-supervised learning and multimodal machine