26 data "https:" "https:" "https:" "https:" "Dr" "UCL" research jobs at Imperial College London
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by the Medical Research Council, that aims to improve the standardisation, modelling, and analysis of prescription data in Parkinson’s disease, with the goal of predicting medication-related side
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Associate (post-doctoral) is to conduct world-leading research on Neuro-Symbolic Debates for Safeguarded Generative AI, under the direction of Prof Francesca Toni, in collaboration with Dr Soteris Demetriou
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primary supervision of Dr Thomas Ouldridge. The student will develop predictive models of nucleic acid strand displacement rates to allow the rational design of complex networks of ever-increasing
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the protocols used to control and communicate sensitive patient information, all the way up to interventional devices and systems for personalised healthcare. We are particularly looking for an IC
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healthcare interventions. You will design and deliver cost-effectiveness and budget impact analyses, analyse healthcare cost and outcomes data, and develop decision-analytic models. Working closely with
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primarily report to Dr Rhea Liem and Professor Rafael Palacios. If you require any further details on the role please contact: Rhea LIEM – r.liem@imperial.ac.uk. Please note that job descriptions are not
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worldwide, and with the rise of antimicrobial resistance (AMR), the need for new preventive strategies is urgent. As a Fleming Initiative Clinical Research Fellow in Dr Dinesh Aggarwal’s group, you will be
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supervisors Dr. Andrew Scott (imaging physics), National Heart and Lung Institute/RBH and Professor Denis Doorly (computational modelling), Aeronautics, Imperial. The research will develop our computational
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gas challenges. You will particularly gain skills in the principles and practice of running mechanistic clinical studies from practical aspects through to handling data. In addition to supporting
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and managing aspects of an academic lab Proven track record of research in their area of expertise on alternative proteins or closely related area Experience in analysing biological experimental data