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Computational Mathematics for reliable and trustworthy uncertainty quantification in science, engineering, and machine learning. Your workplace You will be employed at the Division of Applied Mathematics in a
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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of separating fire-induced signatures from natural environmental variability (weather, canopy changes, tree motion) and fluctuations in the SoO sources themselves. Machine-learning methods will help improve long
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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Interaction venues. For further information about the project, see: https://www.nordforsk.org/projects/nordic-perspectives-collaborative-ai-blue-collar-work-cai-blue. Your competencies You must hold a master’s
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quantification in science, engineering, and machine learning. Your workplace You will be employed at the Division of Applied Mathematics in a welcoming and international work environment. The research group in
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours
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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
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engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 5 Feb 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not
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., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by