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writing and electronically and prepare proposals and applications to external bodies. Applicants will possess, or be nearing completion of a relevant PhD, or possess an equivalent qualification/experience
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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for deep access within the human body. The research remit will encompass: mechanical and electronic circuit design, prototyping, and pre-clinical evaluation of diagnostic and therapeutic devices to tackle
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Clifton (email: david.clifton@eng.ox.ac.uk ). For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ . Only online applications received before midday on the 18
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methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David Clifton (email: david.clifton@eng.ox.ac.uk). Only online applications received before
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be organised, highly motivated and able to work independently as well as part of a team. Informal inquiries about the position can be sent to Prof. Ivan Ahel via email: ivan.ahel@path.ox.ac.uk
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pressure by using graphene membranes as X-ray and electron transparent windows to separate a liquid/gas environment from the vacuum conditions typically needed (see 10.26434/chemrxiv-2025-0cgp0). This role
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known for our pioneering research and pride ourselves on our international reputation. We are equal first in the UK for the impact of our Computer Science research, and second for our Electronic
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instrumentation often located at synchrotron facilities. We have recently developed operando cells which can perform XPS measurements at > 1 bar pressure by using graphene membranes as X-ray and electron
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion