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; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 9 hours ago
PhD studentship in the Groups “Numerical Analysis and Scientific Computing” and “Mathematics Applied to Biology” at the University of Sussex (UK). PhD project Statistical inference has proved to be
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diminished, e.g. though ageing or a physical interface such as a sock or glove. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant
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materials, has led to significant theoretical advances on the mathematical description of fabric anisotropy for monotonic loading. However, the quantification of fabric anisotropy during cyclic loading is
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and local communities. Essential: 1- Bachelor/MSc degree in Mathematics, Biostatistics, health informatics or any computational research degree 2- The student should be proficient in one
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, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working Families, and sponsors of International
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Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity and or impulsivity. The diagnosis and monitoring of the symptom severity are mostly based on subjective reports, while neuropsychological testing and...
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foundation in mathematical and control theory is essential for conducting this research. The applicant should have a relevant degree, ideally with a background (or strong interest in developing knowledge) in
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control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong foundation in mathematical and control theory is
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of Discrete Element numerical modelling on idealised granular materials, has led to significant theoretical advances on the mathematical description of fabric anisotropy for monotonic loading. However, the
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or 2nd class hons degree in computer science, biomedical engineering, physics, mathematics or related subject PhD qualified in computer science, biomedical engineering, physics, mathematics or related