36 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" positions
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multiple competing demands will be vital. The candidate will be committed to UCL’s values of inclusivity, respect, collaboration, and sustainability. What we offer Visit https://www.ucl.ac.uk/work-at-ucl
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: https://www.ucl.ac.uk/bartlett/energy/research/shipping and www.shippingandoceans.com UCL is part of a consortium of eight universities leading on the maritime component of TransiT, a new UK research hub
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of the following UCL EEE academics: Dr Laura Toni Dr Francesca Boem Professor Miguel Rodriguez Dr Eduardo Pignatelli Applicants are encouraged to review these supervisors’ profiles and research outputs, and may
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funded by the Medical Research Council until 31 December 2026 in the first instance. For a full job description please visit UCL’s online recruitment portal (https://www.ucl.ac.uk/work-at-ucl/search-ucl
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• Enhanced maternity, paternity and adoption pay • Employee assistance programme: Staff Support Service • Discounted medical insurance Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out
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Social and Historical Sciences. For more information, please visit http://www.ucl.ac.uk/about UCL Mechanical Engineering UCL Mechanical Engineering has been pioneering the development of engineering
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Social and Historical Sciences. For more information, please visit http://www.ucl.ac.uk/about UCL Mechanical Engineering UCL Mechanical Engineering has been pioneering the development of engineering
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laboratory upkeep. The post is available from 05 January 2026 and is funded by the Sigrid Rausing Trust as part of a UCL Neurogenetic Therapies Programme award for one year in the first instance. If you need
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description. This position comes with an additional market supplement of £20,000 per annum, pro rata. For information on UCL's salary scales, please visit https://www.ucl.ac.uk/human-resources/employees/pay
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with UCL Chemical Engineering and work closely with experts in in-silico engineering and applied machine-learning (Dr Francois Sicard), complex multiphase flows (Prof Panagiota Angeli), and pharmacy