University of Cambridge PhD Studentship - Machine Learning Computational Biology 2017, UK


Deadline:

June 10, 2017

Disciplines:


Opportunity Cover Image - University of Cambridge PhD Studentship - Machine Learning Computational Biology 2017, UK

PhD Studentship - Machine Learning Computational Biology (Fixed Term)

Candidates are invited to apply for a PhD position in Computational Biology in the Department of Medicine and Microsoft Research Cambridge supported through the Microsoft Research PhD Scholarship Programme.

The position will be co-supervised by Professor Andres Floto (Molecular Immunity Unit, Department of Medicine University of Cambridge) based at the MRC Laboratory of Molecular Biology, Cambridge, and Dr John Winn (Principal Investigator, Machine Learning and Perception Group, Microsoft Research, Cambridge UK) and is focused on modeling infective exacerbations in Cystic Fibrosis.

Cystic fibrosis (CF) is the most common life-limiting genetic disorder in the UK (affecting over 10,000 individuals) and leads to chronic respiratory infections, progressive airway inflammation and eventually death. Sudden clinical deteriorations (termed acute pulmonary exacerbations; APEs) are the single most important cause of CF morbidity and mortality, but very little is known about what triggers APEs and how to predict them.

The aim of this project is to use the large dataset of daily physiological telemetry recordings and longitudinal clinical metadata collected through the UK SmartcareCF study (PI Floto) to develop generative graphical models of the processes leading to APEs to i) gain insight into the pathophysiology of APEs, which might subsequently be testable clinically or experimentally, and ii) develop algorithms that might predict the onset of APEs, which could potentially be used clinically to trigger early antibiotic therapy.

The student will first refine existing dependency graphs of the underlying pathological and physiological processes underlying APEs into a fully specified graphical model consistent with the latest clinical understanding. Suitable machine learning tools, such as the Infer.NET framework will be applied to this model to infer the underlying factors influencing APEs, in a similar fashion to existing work on graphical models of asthma (Simpson et al., 2010 AJRCCM 181:1200-6) and of lung function (Chiappa et al., 2013 Respir Res. 14:60). With this physiological model in place and verified, the student will extend it to encompass processes that are potential triggers for APEs with the aim of inferring the nature and influence of these trigger processes.

The scholarship will provide a total bursary of £30,450 GBP paid in annual installments over four years including a one-time fixed payment for a Laptop and Conference/Travel Reimbursement

Fixed-term: The funds for this post are available for 4 years in the first instance.

The deadline for applications is 10th June 2017. Informal enquires regarding this studentship may be made to Andres Floto (arf27@cam.ac.uk) or John Winn (jwinn@microsoft.com).

All cover letters and CV's should be sent to Andres Floto (arf27@cam.ac.uk).

Interviews are planned to be held in mid-June 2017.

Please quote reference RC12155 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

For more information please click "Further Official Information" below.



Eligible Countries
Host Country
Study Levels
PhD
Opportunities
Publish Date
June 02, 2017
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