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WMS MRC Doctoral Training Partnership

Precision Diagnostics & Data Analytics

A.2

These studentships offer the opportunity of PhD research in applied translational biomedical or healthcare research using novel techniques in Precision Diagnostics and Data Science. The generation of large and complex datasets derived from high-throughput molecular and cellular data (genomics, proteomics and metabolomics), biological and medical imaging to population level data (including epidemiology) is transforming our understanding of the complex environmental, social and molecular determinants of disease. The adoption of new techniques and approaches in artificial intelligence, machine learning and data science will enable greater automation, quantitation and ability to extract important information from these datasets, that will lead both to improved understanding of disease and new approaches for its prevention and therapy. Visit these links for more information:

Project supervisors (listed alphabetically)

  • Alex Baker (Chemistry) l My lab develops lateral flow diagnostics for neglected tropical diseases, primarily snake bites. We do this by applying synthetic chemical and analytical techniques to design biomimetic alternatives to antibodies. We collaborate closely with Gabriele Sosso and Seb Perrier.
  • Andrew Blanks (Medical School) l We are interested in the in silico reconstruction of myometrial physiology by integrating large data sets of histological micro-architecture with spatially resolved transcriptomics. l working with: Magnus Richardson (Mathematics Institute)
  • Till Bretschneider (Computer Science) l We are interested in image based modelling of cellular dynamics, particularly the actin cytoskeleton, cell motility and macropinocytosis using fast 3D lightsheet microscopy, quantitative image analysis/machine learning and mathematical modelling l working with: Andrew McAinsh (Medical School)
  • Nigel Burroughs (Mathematics Institute) | My lab designs algorithms for analysis of complex, dynamic data and for data-driven mathematical modelling in chromosome behaviour, reproductive health, cancer therapy (chronotherapy) and T-cell immunology (vaccination modelling). I work with Andrew McAinsh (Medical School)
  • Alex Cameron (Life Sciences) l We investigate the structures of membrane transporters and channels using a combination of X-ray crystallography and cryo-EM. We work with both Manuela Tosin (Chemistry) and Nick Dale (Life Sciences)
  • James Covington (School of Engineering) l We develop new precision diagnostics tools for the detection and monitoring of gastroenterological disease and the use of gas phase biomarkers emanating from biological waste (e.g. breath, urine and stool) to understand changes within the gut and align these to more stratified patient care. We work with colleagues at UHCW and industry partners
  • Ann Dixon (Chemistry) l My laboratory investigates the molecular and biochemical details of antibody-antigen immune recognition and develops antibody fragments for human disease detection and monitoring in collaboration with our industry partner Global Access Diagnostics 
  • Mark Elliot (Warwick Manufacturing Group) My lab uses motion-capture and wearable sensor technologies to detect and analyse movement-related health conditions, including osteoarthritis. We work with Michael Backhouse (Medical School), Theo Arvanitis (WMG), Nicole Tang (Psychology) and Richard King (UHCW).
  • Daniel Hebenstreit (Life Sciences) l We use using next generation sequencing and mathematical modelling to understand the molecular mechanisms of transcription and its interplay with nuclear topology in disease. We work in collaboration with: Karuna Sampath (Medical School) and Matthew Turner (Dept of Physics)
  • Alex Jones (Life Sciences) l The Proteomics Research Technology Platform (RTP) helps researchers use mass spectrometry to study high throughput protein identity, quantity, modifications, interactions and complex formation in both pathogenic bacteria and mammalian cells.
  • Julie Macpherson (Chemistry) l We develop point-of-care sensors, based on electrochemical principles or surface modification, for important health diagnostic analytes in blood. We work in collaboration with: Dr. Nick Matharu and Dr. Prakash Satodia (University Hospital Coventry and Warwickshire)
  • Fayyaz Minhas (Computer Science) l We develop bespoke machine learning models for computational biology and digital pathology. We work closely with: Nasir Rajpoot (Computer Science)
  • Masanori Mishima (Medical School) We are developing machine learning tools for automated quality control of in vitro fertilised embryos in collaboration with Geraldine Hartshorne (University Hospital Coventry Warwickshire)
  • Adam Noel (Engineering) l We use mathematical and statistical modelling of biophysical signal propagation, cellular signal processing and molecular communication engineering tools to understand signalling within and between cells l working with: Christophe Corre (SLS/Chemistry) and Anne Straube (Medical School)
  • Sebastien Perrier (Chemistry and Medical School) l Our work focuses on the design of nanomaterials for next generation therapeutics, diagnostics and probes for elucidating the mechanisms involved at the bio-nano interface. We work with: Robert Dallmann (Medical School) and Meera Unnikrishnan (Medical School)
  • David Rand (Mathematics Institute) We use mathematical modelling to understand the link between disruption of the circadian clock to improve chronotherapy and patient survival from cancer. We work closely with Robert Dallmann (Medical School) in a joint project funded by Cancer Research UK.
  • Tara Schiller (Warwick Manufacturing Group) l We investigate late-stage atherosclerosis, following heart attack or stroke, using materials characterisation techniques of patient samples in collaboration with Chris Imray and Sean James (UHCW & Arden Tissue bank) and Karlheinz Peter (Baker Institute, AU)
  • David Snead l (University Hospital Coventry Warwickshire) l We use the PathLAKE data lake to research how artificial intelligence algorithms can be used to predict the presence, classification, prognosis and prediction of cancer and other diseases. We work in collaboration with Nasir Rajpoot (Computer Science)
  • Gabrielle Sosso (Chemistry) l We harness machine learning techniques in conjunction with experimental insight to achieve the rational design of the next generation of cryoprotectants for medical applications l We work closely with Matthew Gibson (Chemistry)
  • Nigel Stallard (Medical School) l We are interested in the statistical design and analysis of clinical trials, including optimal trial design, interim analyses and use of short-term endpoint data for decision-making and development of innovative methods for clinical trials in small populations.

Key Facts

Four-year MSc + PhD fully funded programme

Contact: Tom Hodgekins

Email: mrcdtp at warwick dot ac dot uk

Funding