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  • Fluorescent Deep Space Petri-Pod

    The ‘Fluorescent Deep Space Petri-Pod’ (FDSPP) is a miniaturised hardware solution for performing remotely operated biological experimentation on multiple types of organisms, via fluorescent and white light imaging capabilities in deep space

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    Acta Sanctorum All 68 volumes of the Acta Sanctorum as published by the Société des Bollandistes. The encyclopaedia documents the lives of Saints from 1643 to 1940, organised by each saint's feast day.

  • John Ellis Jones

    The University is saddened to learn of the death on 28 January 2023 of Mr John Ellis Jones.

  • The rocking horse: a classic object of childhood?

    Read the article "The rocking horse: a classic object of childhood?" This is part of the Social Worlds project at the University of Leicester.

  • Endangered Archaeology in the Middle East and North Africa (EAMENA)

    The University of Leicester School of Archaeology and Ancient History Endangered Archaeology in the Middle East and North Africa project

  • Payment methods

    Before making payment  Students are often targeted by fraudsters. The University has a zero-tolerance policy to fraud. If any payment made for a student is found to be fraudulent the student will face disciplinary action, including expulsion.

  • Donor’s legacy will help train future surgeons

    The dying wish of a former surgeon is helping medical students at the University of Leicester to follow in his footsteps

  • Student of the Year nomination for University of Leicester engineer

    Third-year year Engineering student at the University of Leicester Samiksha Raviraja is one of five students shortlisted.

  • Trailblazing woman of leadership is honoured by the University of Leicester

    A University of Leicester stalwart who led the charge for more women in leadership roles has been honoured by the institution.

  • Artificial Intelligence tool successfully predicts fatal heart rhythm

    In a Leicester study that looked at whether artificial intelligence (AI) can be used to predict whether a person was at risk of a lethal heart rhythm, an AI tool correctly identified the condition 80 per cent of the time.

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