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Field
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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proteins as food ingredients in food models Conduct project reporting and publishing results in international scientific journals Participating in teaching and supervision of students at all levels As a
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, Physics, Geosciences or a closely related field Experience with mathematical inverse methods, global geo-/paleomagnetic field modelling expertise is an advantage Knowledge of geomagnetic field evolution
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Criteria: Qualifications A good first degree in Physics or Mathematics. A PhD (or be close to submission) in Theoretical or Mathematical Physics or a related subject. Experience Experience in conducting high
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to disseminate research results QUALIFICATIONS Applicants must have (or be about to receive) a PhD in physics, biophysics, systems biology, applied mathematics, bioengineering, chemistry, chemical engineering, or
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outside Duke University. Preferred qualifications: PhD (completed in the last 1-5 years or PhD candidate) in a quantitative discipline, including Computational Biology, Bioinformatics, Computer Science
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Requisition Id 14907 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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. Proficiency in frameworks like Pyomo and/or TensorFlow/Pytorch/Keras Solid foundation in mathematics/statistics, with experience in cyber-physical systems modeling. Ability to work both independently and
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, computer science, mathematics and engineering sciences in general. DTPA’s research focuses on developing quantitative and analytical theories, alongside advanced methodologies rooted in mathematical modeling
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine