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Biological & Medical Sciences PhD Projects, Programs & Scholarships in St Andrews

We have 14 Biological & Medical Sciences PhD Projects, Programs & Scholarships in St Andrews

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  Inter-specific Interactions: investigating the role of grey seals in the harbour seal decline
  Research Group: Scottish Oceans Institute
  Dr D Russell, Prof P M Thompson, Dr GD Hastie, Dr A Brownlow
Application Deadline: 4 March 2019
The UK hosts two species of seal. the harbour (Phoca vitulina) and grey seal (Halichoerus grypus) which are key top predators in UK seas.
  Harnessing Cell-Mediated Immunity to Cytomegalovirus for Personalized Antiviral Therapy
  Research Group: Biomedical Sciences Research Centre
  Dr MM Nevels, Dr SJ Powis
Application Deadline: 24 February 2019
Human cytomegalovirus (CMV) establishes lifelong latent infections in most of us. Although CMV does not usually cause severe disease in healthy people, the virus is a leading cause of birth defects and a major pathogen in individuals with weakened immune systems including transplant patients.
  PhD in the Biosynthesis and Enzymology of Fluorine Containing Metabolites in Streptomyces Bacteria
  Prof D O'Hagan
Applications accepted all year round
Research in the O’Hagan group has had a focus on the biosynthesis of fluorine containing natural products and the identification of a fluorination enzyme, ‘the fluorinase’, from Streptomyces cattleya.[1] Fluorine is very rare in nature, and in those rare cases where an organism can form a C-F bond from fluoride ion, then the enzymology is unique and interesting.
  IAPETUS DTP projects in the School of Geography and Sustainable Development
IAPETUS is the North East of England's and Scotland's multidisciplinary Doctoral Training Partnership (DTP) for the environmental sciences, which is funded and accredited by NERC.
  Estimating numbers of molecular ‘species’ in a tissue
  Research Group: Division of Statistics
  Prof A Lynch, Dr H Worthington
Applications accepted all year round
An experiment to profile e.g. proteins or messenger RNAs will capture a sample of those molecules. There will be a random element to the sample but, depending on the technology used, there will be characteristics that influence the chances of seeing a particular molecule.
  Object classification from mobile and static sensor feeds
  Research Group: Centre for Research into Ecological and Environmental Modelling
  Dr C Donovan
Applications accepted all year round
The demand for video processing is rapidly increasing, driven by greater numbers of sensors with greater resolution, new types of sensors, new collection methods and an ever wider range of applications.
  Modelling population dynamics from detection survey data
  Research Group: Centre for Research into Ecological and Environmental Modelling
  Prof L Thomas, Dr R Glennie
Applications accepted all year round
Ecologists collect data on wild animal populations by a variety of survey methods and infer from these how the population changes over time through recruitment, survival, and movement processes.
  Stochastic modelling of populations of interacting cells with complex underlying phenotypes
  Dr G Minas, Dr T Lorenzi
Applications accepted all year round
Individual based models describe the stochastic evolution of interacting individuals-cells with different phenotypes. Reaction networks on the other hand describe the stochastic interactions between different phenotypes-molecular species within a single cell.
  Statistical design and inference for single cell gene expression data
  Research Group: Division of Statistics
  Dr G Minas, Prof A Lynch
Applications accepted all year round
The advances in biotechnology over the last few decades provide great opportunities for a better understanding of how our body works and how to keep it healthy and, through this, how diseases work and how to overcome them.
  Modelling the interface of metabolism, methylation and mitochondria in prostate cancer
  Prof A Lynch
Applications accepted all year round
The interface of metabolism, methylation and mitochondria is of key importance for understanding the aetiology, biology and prognosis of prostate cancer[1].
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