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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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drilling data, digital‑twin methodologies, and AI‑driven optimization approaches to address fundamental challenges in hard‑rock drilling. As a PhD candidate, you will benefit from close supervision, access
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to uncertainties in returned product condition, quality variability, and unpredictable return flows. This PhD project will investigate how artificial intelligence and data-driven decision-support tools can support
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23 Feb 2026 Job Information Organisation/Company Norwegian University of Life Sciences (NMBU) Research Field Environmental science Researcher Profile First Stage Researcher (R1) Positions PhD
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research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position A new PhD fellowship in path signatures, stochastic analysis, and
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drilling, drilling technology, thermomechanical processes, and AI‑driven drilling optimization, as described in the project outline. Develop and apply numerical, analytical, and data‑driven models
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without a master’s degree have until 31.08.2026 to complete the final exam. The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see
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to NTNU’s PhD program in Engineering at NTNU. Good written and oral English skills. PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application
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24th April 2026 Languages English English English The Department of Mathematical Sciences has a vacancy for a PhD Candidate in Mathematical Foundations of Machine Learning for Sequential Data Apply