UNIVERSITY OF SOUTHAMPTON

PhD Studentship: Integrating Genomic Data for Patient Benefit

Location
Southampton, United Kingdom
Salary
£16,000
Posted
29 Jun 2022
End of advertisement period
15 Jul 2022
Ref
1881022AF
Contract Type
Fixed Term
Hours
Full Time

Human Development and Health

Location:  Southampton General Hospital
Closing Date:  Friday 15 July 2022
Reference:  1881022AF

Main Supervisor: Professor Sarah Ennis
Other members of the supervisory team:  Professor Age Chapman
Amount of stipend and fees: ~£16,000
Duration of the award: Four years, full time

Development of novel approaches to integrate medical genomic data with extensive electronic healthcare data to improve diagnoses and precision treatments

Project description:

There is unprecedented potential to learn from existing patient data, such that we can diagnose new patients faster and more accurately define the specific molecular mechanism(s) underlying their disease.

This project will use computer science and programming skills to integrate digital healthcare and genomic data to develop and test informatic tools that guide clinical decisions resulting in better outcomes for patients.

The NHS Long Term Plan and Genomic Medicine Service commitments to harness genomic technology to improve the health of the population mean that we are world-leading in generating vast genomic data on patients with cancer and rare diseases.

Working within trusted research environments, we now have the exciting opportunity to develop and optimise methods to integrate these genomic sequencing data with electronic healthcare records.

Working within the NIHR Southampton Biomedical Research Centre, the project sits within a digital ecosystem centred around translating cutting-edge tools and technologies to improve patient outcomes. The University of Southampton boasts a nationally leading compute cluster; University Hospital Southampton NHS Foundation Trust is recognised as a global digital exemplar. The project will test and implement novel genotype-to-phenotype bioinformatic approaches using AI techniques (knowledge inference and machine learning), on rich, real-world patient data.

Closing date for applications: Friday 15th July 2022

Please contact:  Professor Sarah Ennis (s.ennis@soton.ac.uk)

Person Specification:  See link here

The successful candidate will have strong informatic skills (programming, mathematics, computer science) and be motivated to understand molecular mechanisms of genetic disease at the patient level.  A keen grasp of genetics and sequencing technologies will be essential for effective processing and interpretation of genomic data. Sitting at the interface of computer science, medicine and genomics, effective communication with multidisciplinary colleagues will be essential.

Applicants should be self-driven, have excellent organisational skills, and be motivated by the potential to impact the health of individual patients and their families

The project applies informatic skills to large-scale biomedical data and so candidates should have or expect to obtain at least an upper second-class degree in a relevant discipline (computer or biomedical sciences, bioinformatics). Applicants with abilities and experience more specific to either one of these diverse sectors (i.e. mathematics/programming versus genomics/biomedicine) should be able to demonstrate an appetite and aptitude to acquire new skills.

You will meet the University of Southampton’s person specification for PhD candidates, which incorporates a full equality, diversity, and inclusivity policy.

Funding information:

Due to funding restrictions this position is only open to UK applicants.

Amount of stipend and fees: ~£16,000 plus fees at UK rate only.

Administrative contact and how to apply:

Please complete the University's online application form, which you can find here

You should enter BRC/UoS/202223/842 as your proposed supervisor. To support your application provide an academic CV (including contact details of two referees), official academic transcripts and a personal statement (outlining your suitability for the studentship, what you hope to achieve from the PhD and your research experience to date).

Please note:

  • You must state project code DHS1 in the Personal Statement section of the online application.
  • The online application references an Application Assessment Fee which is not required for this studentship as it is a postgraduate research degree.

Informal enquiries relating to the project or candidate suitability should be directed to Professor Sarah Ennis (s.ennis@soton.ac.uk)

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