CAMHS Digital Lab Junior Developer

Job Description

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 – sample size investigation for clinical texts classification using NLP

A team in BHI is looking for a motivated research assistant to work on a project investigating optimal sample size for Natural Language Processing (NLP) classification tasks that require manual annotations. The tasks involve:

·       running simulations using deep learning models to investigate model performances in various language settings and training corpora sizes;

·       developing a GitHub project page and a well-documented code;

·       participating in dissemination activities (e.g. preparing and participating in an interactive online seminar).

A successful candidate can start as soon as possible and work till the end of July, in a collaboration with myself, Angus Roberts, Jaya Chaturvedi, and Daniel Stahl. The hours (14h/week) can be worked as two full days or spread over the week, remotely or in the office (Denmark Hill). Please write to to express your interest.

Project Description: Natural Language Processing methods are widely applied to extract information from clinical texts and present it in a structured way. However, unlike in statistical data analyses, there are no methods available for estimating the sample size needed. Our project aims to assess optimal sample size for the development of clinical NLP models and how these requirements change depending on the documents and language properties. By taking a simulation approach and following modern guidance on model validation, we will be able to investigate model performances in various scenarios and provide guidance on sample sizes for clinical NLP tasks.


The role is suitable for a current MSc/PhD student/postdoc/early career researcher in Computer science, Engineering, Health Informatics, Statistics, or a related field.


·       Strong analytical skills;

·       Knowledge of Python programming language;

·       Understanding model validation techniques such as cross-validation and evaluation metrics such as AUC-ROC/sensitivity/specificity/precision, 

·       Ability to work independently and in a team.

London South Bank University (LSBU) is excited to be seeking a skilled, enthusiastic and inspiring individual to join its Research & Innovation Services (RIS) department in the role of Business Systems Support Lead. 

With responsibility for third stream income, RIS (known externally as South Bank Innovation) helps LSBU bring knowledge to life. We drive businesses, individuals and partners to connect with an increasing range of funded and commercial opportunities, inspired and supported by our academics. In turn, we are developing a wider network of relationships integral to the future strategy and success of the LSBU Group: focused on tackling social, economic, and environmental challenges; delivering real-world outcomes and solutions that have a tangible impact. 

The Opportunity: 


This key position offers the successful candidate a rare opportunity to make a real difference in a small but high performing, driven and committed team; busy but always open to new ideas and ways of working together to achieve our goals. 

As our systems and information lead, working with delegated authority alongside our Business Systems Support Officer, you will consistently deliver outstanding service across a range of initiatives focused on the below broad objectives: 

  • Develop and deliver efficient and effective systems, processes and reporting that enhance productivity, increase control, and create new insights for research and enterprise income and impact 

  • Drive systems development, integration and automation, as well as support cultural change through coaching and accessible guidance to ensure rapid and enthusiastic adoption of new systems and processes 

  • Support RIS in becoming an exemplar Professional Service Group (PSG), demonstrating best practice in its approach, behaviour and use of technology 




About You: 

We are looking to hear from candidates with the following skills/experience:  

  • Applied interest in technology, data (insights) and process (improvement) 

  • Numerate and detail-oriented, able to confidently report on complex datasets 

  • Excellent time and task/project management skills; able to prioritise demands/workload to consistently meet often competing deadlines 

  • Excellent interpersonal and communication skills, demonstrating a creative and enthusiastic approach to collaboration with a range of people at all levels 

  • Proven experience/technical proficiency across: Microsoft 365 (Excel, Teams, Forms, SharePoint, Visio, Loop), HubSpot/CRM and Power BI (or similar) 

The ideal candidate will be confident, empathetic and resilient with a proven ability and commitment to delivering outstanding customer service. They will also be naturally well-organised, able to both follow instruction and use own initiative, working proactively and collaboratively across individual and shared goals/purpose. 

A natural organiser, you will be keen to get things done – but done right and to the highest standard – always asking how we can improve how we operate. 

  • 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