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. Qualifications: • A PhD in applied mathematics, statistics, electrical engineering or computational sciences completed within the past 5 years (or soon to be completed) • Experience in numerical analysis and
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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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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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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
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: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Candidates should provide CVs in the EuroPass format, and include language skills. Applications received after
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Criteria: Qualifications A good first degree in Mathematics, Physics or a related subject. A PhD (or be close to submission) in Applied Mathematics, Solar Physics, or a related subject. Experience Experience
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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. The file must include: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Statement of experience with scientific coding/development of numerical methods and
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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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for a hard-working candidate. Qualifications Required skills A PhD degree within statistical genetics, applied mathematics, computer science, medicine, psychology, molecular genetics, or similar. Advanced