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will develop models to understand non-equilibrium transport of orbital angular momentum in superconducting hybrid structures. This is part of an effort to determine the merits of superconducting
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of quantum condensed matter physics and has a duration of three years. Your immediate leader will be the Head of Department. Duties of the position The candidate will develop models to understand non
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of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no ), a center for
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attachment. Main tasks Develop machine learning models to produce forest information at local and landscape scales Develop machine learning models for sustainable forest management Compare machine learning
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, and submit a copy of them as an attachment along with the electronic application/CV. We use Semac background checks on final candidates as part of our recruitment process. ... (Video unable to load from
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include: Transcripts and diplomas for Bachelor's and Master's degrees CV Copy of Master's thesis. If you have recently submitted your Master's thesis, you can attach a draft of the thesis. Documentation
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electron microscopy analysis, Raman spectroscopy, fluid inclusion analysis, potentially appropriate petrochronological methods, and 3D geological modelling. The project will be conducted in partnership with
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, you must bring certified copies of certificates and diplomas upon request. The application must include: Transcripts and diplomas for Bachelor's and Master's degrees CV Copy of Master's thesis. If you
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/SinglePageApplicationForm.aspx… Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications Professional skills Experience in: Reinforcement Learning (RL), Model Predictive Control (MPC
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Norwegian language technology. The goal is to develop responsible technological solutions to societal challenges like AI, fake news, echo chambers, and political polarisation. The results will be new digital