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Field
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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focus on power electronics and control technology as well as a subsequent PhD in a related field, ideally involving system modelling and/or power electronic systems Proven experience in modelling and
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the activities of the Representation Theory and Algebraic Combinatorics Unit. Qualifications: (Required) 1. PhD in Mathematics. 2. Speaking/Listening Proficiency in English. Report to: Dr Liron Speyer
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are looking for: a highly motivated researcher with at least 3 years of research experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs
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Qualifications Essential Qualifications • PhD in mathematics, science or STEM education research or equivalent (e.g., PhD in biological field with dissertation on discipline-based education research) • Experience
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; representation from three continents). Our lab’s strength lies in integrating multiple disciplines: Single-cell microfluidics Quantitative (image) analysis Mathematical modelling Microbiology Molecular biology We
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, Mathematical Modelling and Self-Learning Systems, and Data Science and Analytics as well as a strong PhD programme. The Mathematics Group comprises nine permanent members of staff working across the areas
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of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with experience in mathematically rigorous
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, is seeking highly motivated candidates for multiple postdoctoral positions. We are specifically looking for candidates who possess a strong background in theoretical and computational modeling
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques