PhD Studentship: Genomic prediction of antimicrobial resistance spread

This position is now closed
An opportunity has arisen for a D.Phil. (Ph.D.) place on the BBSRC-funded Oxford Interdisciplinary Bioscience Doctoral Training Partnership in the area of Artificial Intelligence, specifically Predicting the spread of antimicrobial resistance from genomics using machine learning.

If successful in a competitive application process, the candidate will join a cohort of students enrolled in the DTP’s one-year interdisciplinary training programme, before commencing the research project and joining my research group at the Big Data Institute.

This project addresses the BBSRC priority area “Combatting antimicrobial resistance” by using ML to predict the spread of antimicrobial resistance in human, animal and environmental bacteria exemplified by Escherichia coli. Understanding how quickly antimicrobial resistance (AMR) will spread helps plan effective prevention, improved biosecurity, and strategic investment into new measures. We will develop ML tools for large genomic datasets to predict the future spread of AMR in humans, animals and the environment. The project will create new methods based on award-winning probabilistic ML tools pioneered in my group (BASTA, SCOTTI) by training models using genomic and epidemiological data informative about past spread of AMR. We will apply the tools collaboratively to genomic studies of E. coli in Kenya, the UK and across Europe from humans, animals and the environment, Enterobacteriaceae in North-West England, and Campylobacter in Wales. Genomics has proven effective for asking “what went wrong” in the context of outbreak investigation and AMR spread; here we will address the greater challenge of repurposing such information using ML for forward prediction of future spread of AMR. Scrutiny will be intense because future predictions can and will be tested, raising the bar for the biological realism required while producing computationally efficient tools.

Attributes of suitable applicants: Understanding of genomics. Interest in infectious disease. Some numeracy, e.g. mathematics A-level, desirable. Experience of coding would help.

Funding notes: BBSRC eligibility criteria for studentship funding applies (https://www.ukri.org/files/legacy/news/training-grants-january-2018-pdf/). Successful students will receive a stipend of no less than the standard RCUK stipend rate, currently set at £14,777 per year.

How to apply: send me a CV and brief covering letter/email (no more than 1 page) explaining why you are interested and suitable by the Wednesday 11 July initial deadline. I will invite the best applicant/s to submit with me a formal application in time for the Friday 13 July second-stage deadline.

Prize PhD Studentships available

I am offering two PhD projects as part of the annual Nuffield Department of Medicine Prize Studentship competition:

• Real-time detection of multidrug resistant tuberculosis and transmission in England
  Joint with David Wyllie, molecular microbiologist, this project is focused on developing statistical methods for recognizing transmission clusters, integrating genomics approaches with molecular typing schemes and developing future-proof taxonomy for strain identification.
  
  
• Tracking future infection threats using genomic data and electronic health records
  Joint with David Clifton, biomedical engineer, this project aims to develop new machine learning and statistical methods to identify genomic markers of antibiotic resistance and susceptibility within various pathogens, to help track future infection threats.

These are fully-funded, four-year awards open to outstanding students of any nationality. Applicants nominate three projects, in order of preference, from the available pool. For how to apply, click here. Only applications submitted through the online system will be considered, but interested applicants are welcome to contact me informally. The deadline for applications is noon, 6th January 2017.

In addition to my projects, the Modernising Medical Microbiology project has announced the following PhD projects as part of the competition:

• Antimicrobial resistance gene/vector transmission across human, animal and environmental reservoirs
  Supervised by Nicole Stoesser, Nicola De Maio and Derrick Crook
  
  
• Healthcare big data and genomics for infectious disease threat detection
  Supervised by David Clifton, David Eyre and Tim Peto
  
  
• Prediction of Mycobacterium tuberculosis drug resistance through genome sequencing clinical samples
  Supervised by Tim Walker and Tim Peto
  
  
• Antibiotic resistance in Tuberculosis: Predicting de novo the effect of individual genetic mutations
  Supervised by Phil Fowler and Sarah Walker

Collaborative PhD and postdoc positions available

Dr Nicole Stoesser, Prof. Derrick Crook, myself and colleagues in Oxford are seeking a postdoc in Microbial Genomics with statistics skills to join a new three-year project investigating antimicrobial resistance in environmental, human and animal reservoirs of E. coli and related organisms. The application deadline is noon Monday 11th July. For more details click here.

Dr Pierre Mahe of bioMérieux in Grenoble, France, is seeking to appoint an industry-linked PhD position developing statistical methods for genome-based characterization of antimicrobial resistance and virulence genes, with a focus on the opportunistic pathogen Pseudomonas aeruginosa. The position involves a secondment here in Oxford. For more details click here or contact Pierre Mahe.