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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi
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biological questions about how cytoskeletal proteins are used by disease-relevant organisms. We have access to excellent facilities such as the Central Oxford Structural and Molecular Imaging centre (COSMIC
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near to completion) in a bioinformatics field, preferably related to cancer biology. Ideally you should have expertise in spatial biological approaches. You should have advanced skills in code generation
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in and knowledge of the broad area of soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps, and familiarity with colloid
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coding experience (both Python and C/C++), and a record of working in a Linux environment and related scripting languages. What we offer At the university of Oxford your happiness and wellbeing at work is
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Multiphysics software (COMSOL and/or Abaqus), python/matlab coding and Molecular Dynamics Simulator (LAMMPs). 4. Publications in mechanical metamaterials, soft robotics, or related area in peer-reviewed
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to the supervision of graduate students working on the project - Contribute to the preparation of academic publications. - Contribute to code development efforts in the group at large About you The
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deploy models symbiotically with experimental researchers to optimise design and manufacture of Li air electrodes and cells. This will include image-based modelling of electrodes, and finite-element
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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exploring B cell migration in the spleen. The successful candidate will have extensive experience in handling and processing live spleens and an established expertise in live imaging of this organ. As a