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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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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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-term carbon cycle and over the coming century. This PDRA position will focus on model approaches to quantifying CO2 exchanges associated with chemical weathering associated with the warming cryosphere
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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electronically through our online recruitment system and provide the following documents in English: For Doctoral Researcher position applicants: Motivation letter – including contact information (max. 1 page
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of liver micrometastases development in cancer, based on a novel MRI approach which combines multi-dimensional diffusion-relaxometry acquisitions, efficient data denoising and biophysical modelling
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree in Engineering, Computer
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for research funding, including the generation of preliminary data for funding bids by the PI. Supervise students (undergraduate, Masters and PhD students) on research related work and provide guidance to other
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original research on the grid integration of second life battery storage systems. The research will bring together second-life battery modelling, power system optimisation and technoeconomic evaluation