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with large datasets, with a minimum 200 records, using statistical software packages including SAS, R, SPSS, and STATA. (Required) Demonstrated knowledge of at minimum one general object-oriented
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for: Operational research and combinatorial optimization (e.g., solvers Gurobi, CPLEX, Hexaly) Bayesian optimization, evolutionary algorithms, or hybrid methods Multi-objective and constrained optimization Surrogate
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Research Associate to contribute to a project focused on robust Bayesian inference with possibility theory. Robust inference is crucial for many real applications in which datasets are invariably corrupted
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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the team’s work across its different content areas. We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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includes excellent healthcare, retirement plans, tuition assistance, paid time off, and a winter recess. POSITION OBJECTIVE Working under general supervision, the Advanced Data Analytics Research Analyst
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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for health and performance Sports research objectives/questions: WearOptimo has developed a wearable sensor to sense the hydration status of individuals. The sensor uses micro-needles to penetrate the skin and
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. The Assistant/Associate/Full Teaching Professor will develop course content, prepare academic activities and course delivery materials to support course objectives, advise students, work collaboratively to