Grant winners - 9 January 2014

January 9, 2014

Leverhulme Trust

Research Project Grants
Humanities

Isaac Casaubon in England (1610-14): a critical edition of his correspondence

Constructing contemporary history in the Enlightenment: Voltaire historian

Engineering the Byzantine water supply: procurement, construction and operation

Sciences

Self-powered electrochemical promotion of catalysis

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National Institute for Health Research

Improving outcomes in adults with epilepsy and intellectual disability: A cluster randomised controlled trial of nurse-led epilepsy management (EpAID)

Evaluating the effectiveness and cost-effectiveness of dementia care mapping (DCM) to enable person-centred care for people with dementia and their carers: a UK cluster randomised controlled trial in care homes (DCM EPIC trial)

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Allopurinol and cardiovascular outcomes in patients with ischaemic heart disease

  • Award winner: Andrew Hayward
  • Institution: University College London
  • Value: £431,356

Pandemic influenza: population susceptibility, severity and spread. Rapid research using the Health Survey for England

 

Royal Society

University Research Fellowships

Novel topological phases and exotic particles in condensed matter

Unveiling structural assembly and regulation of cyanobacterial carboxysomes

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Action Medical Research

  • Award winner: Michael Duchen
  • Institution: University College London
  • Value: £192,243

Mitochondrial disease: developing new treatments for children

In detail

Award winner: Andrew Peet
Institution: University of Birmingham
Value: £194,548

Brain cancer: improving diagnosis using scanning technology

Every year in the UK, about 400 children are diagnosed with brain cancer. Although current treatments can save lives, they can also cause serious, long-term side-effects. Andrew Peet is aiming to tailor treatment more closely to individuals’ needs. By using a sophisticated technique that provides information on the chemical make-up of tumours, he hopes to gain more information about the patient’s condition from MRI scans. This could enable earlier and more accurate predictions of how aggressive each cancer is likely to be.

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