Grant winners - 24 July 2014

July 24, 2014

Action Medical Research

Research Training Fellowship

Germ cell cancers: protecting children from the side-effects of treatment and saving more lives


Royal Society

Wolfson Research Merit Awards

Awards are worth £10,000-£30,000 a year, which is a salary enhancement

Spin ice and magnetricity

Radar-tracking the spatial movement patterns of key pollinators

Defining the molecular choreography of the inflammatory response


Leverhulme Trust

Research Programme Grants

Knots in nature: DNA, the knotted molecule of life

Scientific properties of complex knots

Research Project Grants

Multiple bubble propagation modes in elastorigid models of airway reopening

Convergent synthesis of aconitine

Using repeat proteins to create a toolkit for synthetic biology and biotechnology


Arts and Humanities Research Council

Pathways to understanding the changing climate: time and place in cultural learning about the environment

In detail

Michaela Mahlberg, University of Nottingham

Award winner: Michaela Mahlberg
Institution: University of Nottingham
Value: £200,437 (AHRC contribution)

CLiC Dickens: characterisation in the representation of speech and body language from a corpus stylistic perspective

The CLiC Dickens project aims to demonstrate through corpus stylistics how computer-assisted methods can be used in the study of literary texts and thereby offer insights into how readers perceive fictional characters. Although computer-assisted study of literary texts is not new, approaches that integrate corpus linguistic and literary concerns are rare. It is particularly challenging to address research questions that both move the discipline forward and require the design of new tools. The methods this team employs and develops are situated mainly in the wider field of corpus linguistics, in which digitised versions of texts and customised software are used to find recurrent textual patterns operating both above and below the level of explicit conscious awareness. This innovative approach combines corpus linguistic methods with research questions from cognitive poetics, specifically the way that readers engage in “mind-modelling” in the process of characterisation.

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