Research Associate in clinical data science for

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Research Associate in clinical data science for intensive care
**MEMBERS ONLY**SIGN UP NOW***.
- Faculty of Engineering
Location:
Bristol
Salary:
£34,304 to £38,587 per annum
Hours:
Full Time
Contract Type:
Fixed-Term/Contract
Placed On:
23rd March 2022
Closes:
28th March 2022
Job Ref:
ACAD105946
The role
This is a fixed term position in clinical data science at the **MEMBERS ONLY**SIGN UP NOW***. and is part of an ongoing research collaboration between the **MEMBERS ONLY**SIGN UP NOW***. and the two local NHS trusts, which has been using data driven methods to improve clinical practice on the Intensive care unit since 2014.
What will you be doing?
You will work closely with the NHS and will hold honorary contracts at both University Hospitals Bristol and Weston, and at North Bristol NHS Trust. Your main role will be data harmonisation and linkage of data from two clinical databases (ICNARC and Philips ICCA), to facilitate the transfer of de-identified patient data into the BNSSG Systemwide dataset
. This activity will unlock significant impact pathways for the NHS and will allow us to answer research questions to improve patient health that were not previously possible due to lack of appropriate data (e.g. ‘what are the long-term health outcomes of patients after intensive care’). You will also conduct proof-of-concept machine learning to demonstrate the utility of the data. The long-term vision for this project is to produce a UK-based open-access intensive care research database for the NHS, much like MIMIC in the US
You will work with our existing team of researchers and clinical staff to develop a data specification to ensure that the appropriate data is captured. You will also work closely with data managers and business intelligence teams within the NHS to understand the idiosyncrasies of the relevant EHR data sources. This will ensure that the harmonised data that you produce is of the highest possible quality.
The proof-of-concept machine learning is likely to involve predictive modelling for fluid management on the ICU. However, there will be opportunities to co-create novel research questions with our engaged team of clinical collaborators. You will also spend 30% of your time working with other researchers on our PNEWS
project, which applies machine learning methods to electronic health record data to try to predict clinical deterioration of ward patients in hospitals. Clinical data science is an exciting and accelerating area of research, and we hope to be able to offer you opportunities for career development beyond the scope of this post. 
You should apply if
You have
Strong background in clinical data science and machine learning 
Good knowledge of Phillips ICCA clinical information system for intensive care 
Knowledge of Snomed CT codes 
Proficiency in SQL scripting 
PhD in clinical data science, machine learning or related field
Communication and Interpersonal Skills
Please see the attached job description for further details.
Additional information
For informal queries, please contact: Chris McWilliams,  ****
To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:  ****We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT and BAME communities, to join us.
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