Research Associate in Stroke Phenotyping

Location
London (Greater)
Salary
£38,826 to £45,649, including London Weighting Allowance
Posted
18 May 2022
End of advertisement period
24 May 2022
Ref
046428
Academic Discipline
Clinical, Pre-clinical & Health
Job Type
Research Related
Contract Type
Fixed Term
Hours
Full Time

Job description

We are looking to appoint a post-doctoral Researcher with good programming skills and interest in decision support systems, to join a multi-disciplinary team on the NIHR funded programme, “DECODE: Data-driven machinE-learning aided stratification and management of multiple long-term COnditions in adults with intellectual disabilitiEs”.   

The post holder will be responsible for developing AI technology for reasoning about computable guidelines in the context of multi-morbidities, including design of user-facing decision support technologies.  

 

In this post, initially funded until 30th September 2024, the Research Associate will initially adapt the ROAD2H decision support system to work with a wider set of guidelines and introduce novel guidelines developed by the colleagues from DECODE.  

 

The postholder will have completed a PhD in a computational discipline and have experience and expertise in programming and at least an interest in machine learning (ML), artificial intelligence (AI), or knowledge representation.  They will be someone who thrives in a highly collaborative and interdisciplinary environment, but is able to work independently, solve problems and deliver research to tight deadlines.  The postholder will be well organised and have excellent communication skills.    

 

King’s is committed to fostering an environment of equality, diversity and inclusion.  

 

Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter. 

 

This post will be offered on an a fixed-term contract until 30th September 2024 

This is a full-time post - 100% full time equivalent

 

Key responsibilities

•        Adapting the ROAD2H decision support system to needs of DECODE project

•        Develop a guideline dashboard based on standards such as OMOP

•        Promote reproducible research

 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria

1.      PhD in a computational discipline

2.      Programming skills (Javascript, Python, Java)

3.      Excellent record keeping and commitment to research integrity

4.      Ability to work independently and deliver high-quality, consistent results in a timely fashion.

5.      Excellent written and verbal communication skills

6.      Collegial and keen to learn

7.      Motivated, creative, and able to act on own initiative independently, as well as part of a larger multi-disciplinary team

8.      Committed to equality, diversity and inclusion, actively addressing areas of potential bias

 

Desirable criteria

1.      AI experience

2.      Familiarity with health data

 

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Further information

The School of Life Course & Population Sciences is one of five Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, diabetes, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 91 per cent of our research submitted to the Subjects Allied to Medicine (Pharmacy, Nutritional Sciences and Women's Health cluster) for REF 2014 was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six Departments

 

About the Faculty:

https://www.kcl.ac.uk/lsm/index.aspx 

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