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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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methods to study human bone marrow models using high content imaging approaches. You will lead in designing and establishing new protocols to the laboratory as well as supporting, mentoring and training
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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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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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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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patterns and ability to work under pressure without compromising accuracy will be vital to the success of the project. Desirable qualifications include proven skills in data analysis and some coding
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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
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or image analysis. The post is full time and fixed term until 30 June 2028. The closing date for applications is noon UK time on Friday, 11 July 2025 You will be required to upload a CV and Supporting