My doctoral project explores how changing perceptions of Africa in the early postcolonial era were both shaped and reflected by Western museum practice, with a specific focus on the representation of Nigerian art in museums in Glasgow. The project will foreground the career and thought of Frank Willett, an expert in Nigerian art and the first professional director of the Hunterian Museum and Art Gallery in Glasgow, drawing extensively on Willett's archives held by the University of Glasgow. This archival research will be supported by interviews both of individuals who knew or worked with Willett and those with lived experience of the era immediately preceding and following Nigerian independence in 1960.

This thesis will explore how current literary translation flows between France and the Maghreb (Morocco, Algeria, and Tunisia), redefine la Francophonie as a multilingual, rather than French-speaking, literary space in the twenty-first century. By comparing cultural policy documents to literary texts translated as part of large cooperation programmes during the past ten years, I will investigate (i) why literary translation from and into Arabic became a tool of Francophone cultural policy in France and the Maghreb (ii) how literary translation as a creative process is impacted when tasked with meeting specific cooperation goals and (iii) how (translated) literature and cultural policy currently intersect in reimagining 'la Francophonie'. As such, the thesis will consider literary translations as Francophone texts in their own right, which has rarely been done before. The thesis will further make a methodological contribution to the field of Comparative Literature by exploring how it could use cultural policy and creative industries research methods to better account for the context of production, translation, and circulation of books, notably in postcolonial settings. Reciprocally, the thesis will help identify a key role for Modern Languages research in shaping cultural policy and the creative industries.

Understanding how neural networks implement behavioural decision-making is a fundamental goal of neuroscience. In this studentship, you will apply cutting-edge techniques in neurogenetics and live imaging to explore how a locomotor-related central pattern generator (CPG) selects and implements motor programmes. You will perform live imaging of CPG activity using genetically-encoded calcium indicators in Drosophila larvae. You will then apply and develop computational neuroscience tools for the analysis of live imaging data. Your aims will be to 1) uncover how the architecture of locomotor networks governs how different types of motor patterns are initiated, maintained, and modified and 2) develop new computational methods for 'mining' of large live imaging datasets in neuroscience. You will work with Bayesian network inference algorithms, a powerful computational methodology for revealing network structure. Bayesian network algorithms have been applied successfully to several types of neural electrophysiology data but not yet to live imaging data, thus you will pioneer this approach. This project is unique in that it will be jointly supervised by both a Drosophila motor systems researcher (SRP) and a Computation neuroscientist (AS). The project will be based in Scotland, but depending on student interest, may involve international travel and collaboration with neuroscientists at Janelia Research Campus and Cold Spring Harbor Laboratories in the United States. This project is a CASE studentship. It will also involve working with Cairn Instruments, a leading optoelectronics company based in Kent, UK.

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at www.rcuk.ac.uk/StudentshipTerminology. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

A powerful discovery of Joseph Fourier in the early 1800s was that certain functions could be written as an infinite sum of simple 'wave-like functions'. Such a decomposition is now known as a Fourier series, and has had wide-ranging applications across mathematics and wider science, for example in signal processing and in solving complicated differential equations. The Fourier transform describes how quickly the Fourier series converges, i.e. the decay rate of the amplitudes of the waves in the decomposition as frequency increases. One way of viewing this is that the faster the Fourier transform decays, the more wave-like the function was to begin with. Thus, some geometric information about the original object is captured by Fourier decay. This research project considers the Fourier transform of measures (mass distributions), which are analogous to functions. It is well known that the Fourier transform of a measure encodes a lot of information about its geometric structure, for example concerning its dimension, curvature properties, and arithmetic resonances. We investigate the Fourier transform, and the geometric information it encodes, in several challenging contexts. For example, we consider how it is affected when the original measure is distorted under standard geometric operations, such as projecting a measure in 2 dimensional space onto lines. Similar questions about the Hausdorff dimension of sets and measures are at the heart of geometric measure theory and we will establish Fourier analytic analogues of classical results in this direction. We also consider the Fourier transform in probabilistic settings. Brownian motion is a fundamental random process - first observed as the seemingly random path a grain of pollen follows when suspended in water - and is our archetypal example. We will consider the Fourier transform of natural (random) measures associated with Brownian motion and related processes. Finally, we will consider dynamically invariant measures, where we will use transfer operators and other tools from the thermodynamic formalism to analyse the Fourier decay.