155 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships in Norway
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the Faculty of Medicine and Health Sciences at NTNU. It was established as a Centre of Excellence in 2002, 2012, and again in 2023. Our Centre of Excellence, the Center for Algorithms in the Cortex (https
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techniques to identify the enzymes, as well as protein purification and recombinant protein expression to get hold of the enzymes. The PhD student will be part of the large and international PEP group (https
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grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme: https
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with disabilities. More information about NMBU is available at www.nmbu.no/en Questions about the position Volha Shapaval Professor +47 98418248 volha.shapaval@nmbu.no Where to apply Website https
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral
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https://www.jobbnorge.no/en/available-jobs/job/296771/phd-candidate-in-parasite… Requirements Research FieldBiological sciences » BiologyEducation LevelMaster Degree or equivalent Additional Information
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if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme (https://www.ntnu.no/studier/phet) You must
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the doctoral program from the Faculty of Engineering (https://www.ntnu.edu/studies/phiv ) You
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systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI outputs in a known structure. This