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replacement) project on Limits of Symmetric Computation. The position would suit a candidate seeking to obtain a PhD at the Department. The project seeks to investigate lower bounds on symmetric computation in
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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programme at the University of Cambridge, focusing on modelling exoplanet interiors and atmospheres. The successful candidate will join a vibrant team led by Oliver Shorttle, the Planetary Chemistry group
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diffraction, and differential scanning calorimetry Mechanical performance assessment, including small-scale tensile testing and in situ testing at Diamond Light Source The studentship is fully funded for 3.5
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cutting-edge advanced materials fabrication, simulation and characterization to address the pressing challenge of achieving a sustainable IoT ecosystem. The doctoral candidates will acquire a solid
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-scale data'. It is motivated by the recognition that modern data generating mechanisms can be highly complex, and it is often challenging to write down a plausible generative statistical model. We
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based at the Department of Obstetrics and Gynaecology, University of Cambridge. They investigate the mechanisms by which sub-optimal nutrition in early life can affect reproductive ageing, the impact of
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, and performance testing using techniques such as scanning and transmission electron microscopy, diffraction methods (lab-based and synchrotron), mechanical property assessments, and thermo-physical
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specimens with controlled variations of impurity elements (e.g., Cu, Ni, Sn, Sb, Mo) to assess their impact on microstructure and mechanical properties. The ability to generate thousands of unique
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duties include producing builds of aluminium and steel alloys using LPBF technology; characterise the build microstructure and mechanical behaviour; and use the knowledge gained to devise novel