The post is funded by the British Heart Foundation Research Programme for 4 years. As Research Associate, 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 at the National Heart and Lung Institute, physiologists from 21 Hospitals in the UK, and computer scientists from the Intelligent Sensing and Vision Research Group (https://intsav.github.io) to develop AI techniques applied to cardiac image processing.

The main aim of this cross-disciplinary project is to develop a 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 may also be expected to contribute to the teaching & leaning activities.

Duties and responsibilities

• To refine existing image processing algorithms and develop new algorithms
• Design and implement time-efficient neural network models, so that the system can run in real time
• To take initiatives in the planning of research and directing the work of small research teams
• To identify and develop suitable techniques, and apparatus, for the collection and analysis of data and conducting data analysis
• To ensure the validity and reliability of data at all times
• To write reports for submission to research sponsors
• To present findings to colleagues and at conferences
• To submit publications to referred journals
• To develop contacts and research collaborations within the College and the wider community
• To promote the reputation of the Group, the Department and the College
• To provide guidance to PhD Students

• Contribute to bids for research grants
• To conduct and plan own scientific work with appropriate supervision.
• To maintain highly organised and accurate record of experimental work
• To participate in Group research meetings and internal seminars
• To contribute to the smooth running of the Group’s laboratories and, facilities with other scientists, clinicians, technicians and students within the laboratories
• Assist in the supervision of undergraduate and postgraduate research students and research assistants as required

Essential requirements

• PhD in Computer Science*
• Good understanding of the principles and practical aspects of medical image processing and analysis
• Background in ultrasound image and signal processing
• Experience of dealing with Transthoracic echocardiography
• Practical experience within a research environment and / or publication in relevant and refereed journals
• Demonstrated experience in collaboration with research institutions, commercial companies, and hospital bioengineering units
• Experience in presentation of work at significant conferences
• Experience of working with/maintaining a Virtual Learning Environment (VLE)
• Experience of training and mentoring
• Experience in lecturing, at both undergraduate and postgraduate level, in Artificial Intelligence and Machine Learning

• 
  Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

Further information

This is a Full Time and Fixed Term post offered for 4 years. You will be based at Hammersmith Hospital Campus.

Should you require any further details on the role please contact Professor Massoud Zolgharni (m.zolgharni@imperial.ac.uk).

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £38,194 - £41,388 per annum.

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/

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