131 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Norway
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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
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for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied to machine learning algorithms in order to
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research proposal must be closely connected to the call and the research
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, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools Practical outdoor field experience (e.g
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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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
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models with drone imagery using machine learning techniques and data assimilation. The work will involve collaboration with an interdisciplinary team of researchers, engineers, and local stakeholders in a
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/Qualifications To strengthen our research on the impacts of conflict, PRIO seeks a motivated Junior Data Developer with competence in design and maintenance of databases and machine learning. The successful
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in