54 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in Norway
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5th November 2026 Languages English English English We're seeking a PhD candidate in Biotechnology to tackle antimicrobial resistance. PhD in Bioinformatics and Machine Learning for Infection and
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for probabilistic unsupervised learning for structured biological data. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/307053/3-years-phd-position-in-probabilistic-machine
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try again. UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the
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UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
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SINTEF, Equinor, and Total. The main objectives of the project include the development and the integration of signal processing and machine learning methodologies aiming to improve flow assurance via field
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, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. About the project The role of the PhD candidate will
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Norwegian University of Life Sciences (NMBU), within the Faculty of Science and Technology(REALTEK), invites applications for a PhD position in Applied Causal Machine Learning. The position is affiliated with
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, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage
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engineering disciplines, including structural mechanics, hydrodynamics and machine learning Strong programming skills in Python and/or MATLAB Experience with scientific computing, CFD/FEM software, potential
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and