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Research Assistant – Artificial Intelligence in Cardiovascular Imaging - 5 Years FTC

School of Computing & Engineering

Salary:   £30,078 to £43,472 per annum
Release Date:   Wednesday 01 June 2022
Closing Date:   Monday 27 June 2022
Interview Date:   To be confirmed
Reference:   COMP0038

The University of West London (UWL) is one of the top 40 universities in the UK and the top modern university in London according to the influential Guardian University Guide 2021. 


We were also named University of the Year for Student Experience in The Times and The Sunday Times Good University Guide 2021, being described by the editor as “regularly among the top-performing universities” and proving that “it is possible for a London-based institution to achieve outstanding levels of student satisfaction beyond other universities”.

The School

The School of Computing and Engineering is a dynamic and forward-looking School with high quality teaching, student experience and research informed teaching at the top of its priority list. The School has strong links with local, national and international partners and employability of graduates is the key to courses that we offer. The School enjoys state-of-the-art equipment and continues to invest heavily in its improvement. We offer a number of courses fully accredited by relevant professional bodies across the board.

The Role 

The post is funded by the British Heart Foundation Research Programme for 5 years. As Research Assistant, you will carry out and plan a high quality programme of research in Artificial Intelligence tools applied in cardiac imaging.

You will work alongside a team of cardiologists from Imperial College London and physiologists from 21 Hospitals in the UK, and computer scientists within the Intelligent Sensing and Vision Research Group ( to develop AI techniques applied to cardiac image processing. The main aim of this cross-disciplinary project is to develop an AI-assisted fully automated novel medical technology to be used by cardiologists to assess cardiac function. To this end, a combination of engineering expertise (parallel programming, medical image acquisition and processing), computer science (AI algorithm development, statistics), and clinical experience (cardiology, echocardiography) will be used.

You will also be expected to contribute to the teaching & leaning activities of the MSc Artificial Intelligence, offered by the research group within the School of Computing and Engineering.


The Person

Candidates should have demonstrable experience in AI and Deep Learning developments. Experience in ultrasound and/or medical imaging is desirable. The successful candidate is expected to disseminate their research through presenting at scientific conferences, publishing in peer-reviewed journals, and providing open-source software tools. Candidates should have strong written and oral presentation skills.

In addition to the online application form, you should submit a full academic CV with a list of your recent publications.


How to Apply 


To apply click on ‘Apply Online’ and fill out the application form. Further information about the application process can be found here: 


Interviews are expected to be held in the week commencing Monday 4th July 2022. 


For informal enquiries about the position please contact Professor Massoud Zolgharni, 

Additional Information 


We welcome applications from individuals who do not have a fellowship of the Higher Education Academy (HEA). Should you be successful and do not hold an HEA fellowship you will be asked to complete one within 2 years of appointment as a condition of your continued employment. Depending on eligibility this may take the form of an advanced Level 7 apprenticeship in teaching which means that you will spend 20% of your work in off-the-job study.

Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. 

The University reserves the right to close the vacancy earlier than the published end date should it receive sufficient applications to warrant earlier shortlisting.

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