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Mathematics » Discrete mathematics Researcher Profile Recognised Researcher (R2) Application Deadline 9 Oct 2026 - 21:59 (UTC) Country Sweden Type of Contract Not Applicable Job Status Full-time Is the job
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postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and
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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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project focuses on developing a mechanistic understanding of coupled redox–dissolution pathways in multi-metal oxide systems and how these pathways can be inferred from real-time process signals. Using
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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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the field of Machine Elements. The main aim of this PhD student position is to strengthen the newly started research on Triboelectrictive nanogenerator (TENG)-based smart lubrication in Machine Elements
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generation synchrotron, MAX IV in Lund, Sweden. The successful candidate will contribute to the experimental and theoretical investigation of two-dimensional Pb films coupled to metal and semiconductor
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into the occurrence and mobility of the elements in rocks, soil, and water, focusing on methods to prevent or reduce the environmental impact of metal extraction and infrastructure development. Project description
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are based on the finite element method and advanced material modelling. Work duties The main duty is to conduct research. The project is primarily computational and includes further developing and validating
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-safety theory, crash and injury analysis, road-user behaviour, transport planning or road-infrastructure safety. experience of advanced quantitative methods, such as regression or discrete-choice models