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Field
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statistical shape analysis, Riemannian geometry, time series and stochastic processes, and Bayesian statistics. Key responsibilities: To carry out research within the framework of the project, under
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning to join the Visual Geometry Group (VGG), in central Oxford. The post is funded by Toyota Motor Europe and is fixed-term
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motivated Post-Doctoral Associate to join our team with a strong background in robot control, machine learning, and differential geometry to work on the development of advanced algorithms to enhance
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flow within cerebral aneurysms. Arterial geometries are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann
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microfluidics channels experimentally. The particle dynamics under solute concentration gradient will be analyzed and new methods of manipulating particles in complex geometries will be developed. Application
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The Department of Mathematics is a diverse and growing department with strengths in Algebraic Geometry, Analysis, Combinatorics, Differential Geometry, Mathematical Biology, Number Theory, Representation Theory
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of transferred layers will be characterized by Raman. In a second step, the candidate will participate in the optimization of the device parameters (electrode material, geometry, dielectric...) Requirements: PhD
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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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control. Creating generalizable tools for various battery types, geometries, and chemistries. The scope of methods and applications will be tailored in collaboration with the selected candidate. The work
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technological impact in various systems, extending the study to more complex geometries such as 2D structures and highly multi-modal non-Hermitian devices. Recent studies have demonstrated that a system composed