Computer Vision Research Assistant

Job Description

  • assisting in conducting research activities related to computer vision, including literature reviews, data collection, experimentation, and analysis

  • assisting in the development and implementation of computer vision algorithms, including image processing, object detection, recognition, segmentation, and tracking

  • preparing and annotating datasets for training and evaluation purposes, ensuring data quality and relevance to research objectives

  • contributing to the solution in a form of software tools and frameworks for computer vision research, using programming languages such as Python or C/C++

  • assisting in the analysis of qualitative and quantitative data, as directed.




  • Some prior experience and strong interest in the subject of Computer Vision

  • Understanding of deep learning frameworks (e.g., TensorFlow Keras, PyTorch) and some proficiency in training convolutional neural networks (CNNs) for computer vision tasks.

  • Familiarity in training deep learning models using preprocessed and augmented datasets, monitoring model performance and convergence during training.

  • Practical knowledge in utilizing programming languages relevant to machine learning, deep learning and computer vision (Python 3.4 and above is an absolute must).

  • Experience working with video / image data, including data preprocessing, annotation and analysis using popular libraries (e.g. OpenCV)

  • Knowledge of common evaluation metrics for assessing model performance in computer vision tasks, such as accuracy, precision, recall, and F1 score.

  • Knowledge in web frameworks written in Python (e.g. Flask) is desirable but not essential



This is a position intended for a current KCL student in computer science, informatics or applied statistics or similar subject areas. 

The purpose of the role is to contribute to writing a computing application written in Python that is currently under development.  The computer application will provide a graphical interface for applying topic modelling and searching for key terms in student dissertation projects.  The end goal is to develop a tool that can provide insights into the content of dissertation projects that students are completing on different degree programmes within the faculty. 

This job will involve attending the KCL Denmark Hill campus in-person two days a week initially - there may be some flexibility to work remotely as the project progresses.  This is a discrete project with an assigned maximum number of hours available in the budget (a total of 98 hours).  There can be some flexibility in when/how these hours are worked. However, hours worked cannot exceed 20 hours in any one week.  It is envisaged that the candidate will work two to three days per week on the project for around 7 weeks.  The successful candidate will work closely with the Project Manager, Dr Samuel Evans.

The job application process will involve a short interview.

Key responsibilities:

  • To work under the direction of the project manager (Dr Samuel Evans) to generate a working computer application coded in the Python programming language.

  • To contribute to project planning and delivery.

  • To manage administrative duties related to the project.

  • To liaise with project collaborators.


  • Studying for a BSc or MSc in computer science, informatics, applied statistics or a related area.


The skills and experience required are as follows.



  • Excellent computing skills in Python.

  • Good communication skills.

  • Ability to work independently when required.

  • Good time management and prioritisation skills.


  • Experience/knowledge of applying topic modelling and natural language processing techniques to text data. 

  • Experience of using the Tkinter Python library.

  • Experience in compiling Python software for cross-platform applications.

  • Experience in using Github.

This is an exciting part-time position at the heart of the Child and Adolescent Mental Health Services (CAMHS) Digital Lab led by Dr Johnny Downs (  The CAMHS Digital Lab is a recently formed team within the King’s Maudsley Partnership. The lab will enable KCL researchers, engineers, and designers with SLaM healthcare and digital service providers to work together to develop products which will improve child and adolescent mental health. The post-holder will primarily work alongside the lab’s clinical informatics lead and research platform engineer.


We are seeking a junior developer to join our interdisciplinary team and to support programming projects primarily relating to the optimisation of myHealthE processes.


The myHealthe (MHE) platform is a Digital Health Monitoring System which provides young people and their families, researchers and NHS clinical services the ability to track mental health symptoms of young people over time. It also provides a mechanism for the NHS Trusts to know which families are happy to be contacted by approved researchers for potential enrolment in research studies – a consent for research contact register. The MyHealthE programme is used with South London and Maudsley NHS Foundation Trust (SLaM) Child and Adolescent Mental Health Services (CAMHS) and will be extended across NHS Trusts in London, Nottingham, Sussex and Hampshire offer. To evaluate is applicability to support trial recruitment, MHE is used a platform to help families recently referred to NHS CAMHS to rapidly access online parenting support.


The successful candidate will be someone who is motivated to improve child and adolescent mental health care. They will be positive and professional. The post requires someone with excellent interpersonal and communication skills and have an interest in how programming can enhance processes to improve patient outcomes.


 Grade 7 in computer science


1.           Strong IT skills and knowledge of the whole MS Office suite. 

2.           Excellent communication and interpersonal skills.

3.           Produces work with an eye to accuracy and excellent attention to detail.

4.           Enthusiasm and can-do attitude with a strong work ethic, using initiative and creativity to address challenges.

5.           The ability to apply programming skills to operational service challenges

6.           Assist with developing methods for harmonization and curation of health data from diverse data sources using establish open source solutions and standards


Research assistant to support specific research studies on palliative dementia care, including update of systematic reviews (data extraction, analsyis, reporting and publication), and setup of new national network for dementia care


Systematic reviews: data extraction of identified eligible published evidence; update results including tables and figures and narrative reporting; and preparation for publication. One review is being updated on 'Service level interventions to promote quality of life for adults with dementia in the last 1 or 2 years of life,, and their family carers', and 2nd review results reporting and discussion on 'Individual level interventions for physical wellbeing to promote quality of life for adults with dementia in the last 1 or two years of life'. Supporting setup of new ESRC funded national dementia network on inequalities in dementia care. Coordination of meetings with community partners, lived experts and researchers, planning delivery of activities for year 1, and network promotion e.g. website, social media


Cicely Saunders Institute, Denmark Hill Campus King's College London and remote working


Esstential - BSc in health or social sciences, or relevant area Desirable - MSc in health or social sciences, or relevant area


Expertise in health or social sciences with relevant BSc, and preferrably MSc. Experience in supporting/conducting systematic reviews using narrative synthesis - data extraction and results reporting Experience of supporting research studies in the health or social sciences Interest in long-term conditions, dementia and/or palliative care, desirable