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Field
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for fitting stochastic epidemic models to infectious disease outbreak data. The post will contribute to cutting-edge methodological research on Bayesian inference for complex stochastic transmission models, as
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cumulative impact assessment, related to marine or sustainability challenges Strong analytical and synthesis skills, including experience working with complex interdisciplinary evidence Experience with
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at Kjeller, Lillestrøm. Job description The Martian atmosphere is a dynamic system, shaped by complex physical and chemical processes operating across a wide range of timescales. This PhD project will
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experience in marine technology and AI will be advantageous Knowledge about high performance computing and computational fluid dynamics (CFD) Knowledge about physics-informed neural networks (PINNs) Language
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psychological assessments. Training in professional skills development will also be offered, including guidance in writing grants and papers, assistance in building a professional network, supervising trainees
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dynamic system, shaped by complex physical and chemical processes operating across a wide range of timescales. This PhD project will investigate dynamic phenomena and processes in the Martian atmosphere
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models and other natural language processing techniques applied to language understanding and the next generation of search engines. AI + Health: This area levarages AI to study and solve complex problems
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the opportunity to contribute to the Public Science Lab, the Ethical Data Initiative (www.ethicaldatainitiative.org), the TransforM excellence cluster and the PHIL_OS project (https