142 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in Norway
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; Industry 4.0 and 5.0. System engineering and socio-technical systems AI-supported adaptive continuous learning Industrial cybersecurity, supply chain security Semantic modelling of industrial artefacts
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, energy, food and efficient transport. The Department of Marine Technology is one of eight departments in the Faculty of Engineering. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job
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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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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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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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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