Gut microbiome in Parkinson's Disease and application of machine learning to gut microbiome
Growing evidence indicates a connection between Parkinson's Disease (PD) and the gut. Intestinal disorders, including constipation and inflammatory bowel disease, often precede diagnostic motor symptoms by decades. We are seeking a highly motivated individual to join a collaborative team to understand the role of gut microbiome in PD.
Start date1 July 2022
Funding sourceSurrey Institute for People-Centred AI
A stipend of £15,609 for 2021/22, which will increase each year in line with the UK Research and Innovation (UKRI) rate, plus Home rate fee allowance of £4,500 (with automatic increase to UKRI rate each year). For exceptional international candidates, there is the possibility of obtaining a scholarship to cover overseas fees.
The existing human data, available for the project, will be used to identify potential triggers that may initiate gut-to-brain pathology, and microbiome compositional networks to pursue in further experimental models. The microbiome dataset includes 1000 individuals with PD, 600 age-matched neurologically healthy controls, and 100 with REM sleep behaviour disorder (RBD; a PD prodrome). All subjects have genome-wide genotype data, gut microbiome compositions (16S amplicon or whole metagenome shotgun sequences), and metadata (exposures to environmental toxicants, medical history, diet, medications, gastrointestinal health, body mass index and demographics). To our knowledge, this is the largest PD-microbiome dataset, the only one that combines microbiome data with human genome and toxin exposure data, and which was collected using standardised protocols by a single team, thereby minimizing technical variations that are known to profoundly skew microbiome data.
This particular PhD opportunity is built up on a tight collaboration with Payami lab from the University of Birmingham, Alabama, USA.
The PhD student will be involved in the analysis of shotgun metagenome sequences, along with genome-wide genotypes and clinical and toxicant exposure metadata. This project is a part of a larger ASAP (Aligning Science Across Parkinson’s, https://parkinsonsroadmap.org/) effort and will harmonise and accelerate ongoing efforts to identify the earliest pathological changes associated with PD in the gut, elucidating a critical point in disease aetiology, and new avenues for disease intervention.
Overall, the project comes with ready to analyse existing data, with high chance to deliver high impact publications. The student will be trained on analysis of large datasets using bioinformatics, statistical genetics, and/or metagenomics tools, and will get proficiency in programming in R and /or python. The student will also benefit from the Machine Learning and Data Science trainings provided by the Department of Computer Science. In particular, the courses form our popular MSc in Data Science and Machine learning for healthcare are relevant to this project and the PhD candidate can attend these trainings and access all the teaching materials without any extra costs. The University of Surrey also offers a variety of other professional training courses that will be made available to the successful applicant. The existing collaborative network will provide the candidate exciting opportunities within UK and USA and other research groups internationally.
The acceptance of applications might close before the deadline, if suitable candidate is identified.
All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with Distinction (or 70% average) and a strong interest in pursuing research in this field. Additional experience which is relevant to the area of research is also advantageous.
English language requirements
IELTS minimum 6.5 overall with 6.0 in Writing, or equivalent
How to apply
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Vision, Speech and Signal Processing PhD
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