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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
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, Applied Mathematics, Statistics or related computational field. Superb quantitative background, strong coding skills (e.g., Python, R). Expertise in infectious disease modeling. Strong record of peer
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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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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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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interactive multinational and multidisciplinary teamcovering expertise in molecular biology, cell biology, neuroscience, regeneration biology, mathematical modelling, and robotics. The fundamental questions
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. Qualifications • A good first degree in Physics, Mathematics or a related subject. • A PhD (or be close to submission) in Physics, Mathematics or a related subject. 2
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years), or be close to completing a PhD in engineering or physics, preferably with a focus on the development of fluid-thermal-structure interaction mathematical models. A thesis topic relevant to
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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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(community interventions, community-based participatory research, meta-analysis and bias in research, RCT methods, causal interference, mathematical modeling, and econometrics) Policy research related