Research Associate – Computer Vision

London (Greater) (GB)
Grade 6, £38,304 - £45,026 per annum, including London Weighting
Thursday, 21 January 2021
End of advertisement period
Thursday, 18 February 2021
Academic Discipline
Life sciences
Contract Type
Fixed Term
Full Time

Job description

Research in the newly established Department of Surgical and Interventional Engineering within the School of Biomedical Engineering and Imaging Sciences focuses on developing novel algorithms for interventional image analysis. The primary activity relates to Vitreoretinal Surgery, via a set of grants and a strong collaboration with Moorfields Eye Hospital. Specifically, we are conducting research on the semi-autonomous delivery of regenerative therapies. The project is looking for a research assistant to complement a multidisciplinary team and undertake research on computer vision of retinal images.

The post involves close and active collaboration with researchers, engineers and clinicians to identify clinical requirements and to design and develop robust image analysis software that will address them. Working with established platforms and building on the software and robotics infrastructure already present within our teams is of paramount importance to ensure project cohesion and strong links with the members of the team. 

The candidate should have a PhD awarded in Computer Vision or relevant field, or be near the completion of the PhD. 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. Should the successful candidate be awaiting the award of their PhD, the appointment will be made at Grade 5, spinal point 30 with the title of Research Assistant until confirmation of the award of the PhD has been received. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6, spine point 31.

In addition, a post graduate degree in STEM or equivalent experience is required, and the Research Associate need to be able to demonstrate good computer vision and software development skills. They will also need to be able to demonstrate strong experience in C/C++ or Java programming and Python. Knowledge and experience with PyTorch/Tensorflow and github/gitlab are highly advantageous.

The successful candidate will be able to demonstrate:

  • Good knowledge of computer vision algorithms for image processing.
  • Solid knowledge of computational geometry and modelling.
  • Solid knowledge of and experience using the MATLAB/Python programming languages.
  • Experience in state-of-the-art structure from motion algorithms.

Experience in the following is a plus for this post:

  • Experience with multi-view and multi-camera 3D reconstruction.
  • Machine learning algorithms and frameworks such as PyTorch or Tensorflow.

Key responsibilities

  • Develop, validate and integrate 3D reconstruction algorithms for computer-assisted intervention (CAI) in vitreoretinal surgery.
  • Develop existing or new software packages and create synergies between them.
  • Maintain accurate and up-to date technical and user documentation of the delivered software.
  • Lead or contribute to the dissemination of the research through high impact publications, open-source software and public engagement activities.


  • Work in a highly agile software and hardware development environment.
  • Demonstrate autonomy.
  • Liaise directly with internal and external colleagues in an independent manner.
  • Use initiative, discretion, knowledge and experience in planning, coordination, organisation and problem solving.
  • Manage any ad-hoc projects, as directed by the academic lead which may arise with respect to strategic and/or operational needs.


  • To maintain an awareness and observation of ethical rules and legislation governing the storage and handling of medical data.
  • To maintain an awareness and observation of confidentiality agreements with collaborators and external organizations.
  • To maintain an awareness and observation of appropriate procedures for the disclosure and protection of inventions and other intellectual property generated as part of the post holder's activities and those of other team members working within the project.


  • To support the School's commitment to the prosecution of internationally renowned research.
  • Initiate and manage change successfully, as required.


  • To attend regular project meetings and training courses for professional and personal development as required.

Communication and networking

  • Communicate with a diverse team on a daily basis, understand the needs of researchers and clinicians.
  • Develop and maintain effective working relationships with staff within the School as well as externally.
  • Regularly communicate information in a clear and precise way.
  • Initiate, build or lead internal networks within the School or externally.

Decision making, planning and problem solving

  • Lead in decisions that have a significant impact on their own work, that of others and be party to collaborative decisions.
  • Manage own workload and resources and that of others, prioritising these in order to achieve their objectives.
  • Communicate to management any difficulties associated with carrying out work tasks.
  • Responsible for the planning and leading of significant projects or work streams ensuring the effective use of resources, setting standards and monitoring procedures.
  • Resolve problems where the optimal solution may not be immediately apparent and where there is a need to use judgement to resolve problems that are unpredictable and / or occur infrequently.
  • Plan in advance for peaks in workload.
  • Use own initiative and creativity to solve problems.

Analysis and research

  • Provide documentation and produce reports as required.
  • Lead or assist colleagues in the preparation of scientific papers as required.

Pastoral Care

  • Work within a team on a day-to-day basis and provide mutual support.
  • Mentoring of junior researchers including MSc/Meng/Beng students on graduation projects.

Physical Demands & Working Environment

  • Use of computers and time spent at monitors.
  • Occasional travelling within the UK and abroad.

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.

This is a full-time, fixed-term post offered for one year


Skills, knowledge, and experience

Essential criteria

  • Honours degree (2:1 or above) or equivalent in Mathematics, Engineering, Physics, Computer Science or related numerate discipline
  • PhD (or about to complete) or equivalent in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Physics, Applied Mathematics or other relevant area.
  • Good knowledge of machine learning and computer vision algorithms.
  • Solid mathematical background.
  • Experience in computer programming using MATLAB and Python.
  • Experience in Structure from Motion algorithms and 3D computer vision.
  • Ability to work effectively within a collaborative software development environment with people from a variety of backgrounds.
  • Ability to successfully manage tasks to a deadline and to work calmly under pressure.
  • Ability to analyse problems and proactively identify solutions.
  • Highly developed verbal and written communication skills (ranging from informal 1:1 discussions, formal presentations covering both oral and written skills), including the ability to liaise with staff at a range of levels internal and external to the organisation.

Desirable criteria

  • Experience with Deep Learning frameworks, such as PyTorch, Tensorflow.
  • Experience in image processing, especially multi-camera and multi-view images, for example light-field images or stereo images.
  • Experience of working within a clinical environment or closely with medical staff.
  • Experience in sensor fusion techniques, e.g. Kalman filtering, Particle filtering.
  • A demonstrable record of publications in peer-reviewed Computer Vision/Machine Learning conferences and journals, and record of presenting at scientific meetings.
  • An understanding of image acquisition as well as hands-on experience with multi-camera systems such as stereo cameras, light-field cameras, etc.

Further information 

This post is subject to Disclosure and Barring Service and Occupational Health clearance. 

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