Research Associate – AI Methods within NHS Accelerated Access
The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.
The Turing Health and Medical Science Programme has long-term interests in research study design and evaluation methodology for AI-driven healthcare solutions. It is seeking to contribute to the development of standards for how to evaluate AI in clinical studies within the NHS and internationally. Following a recent NHS AI Award to Kheiron Medical Technologies, a specific novel opportunity has arisen for a two-year research programme that will specifically focus on optimising such standards for the breast cancer screening domain as part of a new Kheiron-Turing collaboration.
Further information about the award:
Four phases of award are available to support AI solutions from initial feasibility to evaluation within NHS and social care settings. The award is a competitive process run by the Accelerated Access Collaborative (AAC) as part of the NHS AI Lab, in partnership with NHSX and the National Institute for Health Research (NIHR). Phase 4 is intended to identify AI technologies that need more evidence to merit large-scale commissioning or deployment. The AAC will work with NHS sites to support their adoption of these technologies, and stress test and evaluate them within routine clinical or operational pathways to determine their efficacy and accuracy, and clinical and economic impact.
We are seeking a Research Associate with experience in one or more of the following areas: clinical trials study design, diagnostic tools evaluation and artificial intelligence, to develop novel methodologies and studies to assess the safety and efficacy of Mammography Intelligent Assessment (Mia), a novel AI breast screening solution, developed by Kheiron Medical on over 3 million images from different mammography modalities and different ethnic backgrounds.
Mia has recently been tested in a large-scale clinical trial in the UK and Europe with 283,000 cases (unseen and unenriched sample size). We are seeking to support the full-time secondment (up to 1.0 FTE) of the Research Associate(s) to the Alan Turing Institute.
The successful candidate will report to the Senior Research Advisor, AI Methods within NHS Accelerated Access who will be appointed through open call and in post prior to this role starting.
As part of the AI award, Kheiron will be conducting a series of studies, including large-scale retrospective trials, reader studies, prospective trials, and post-market surveillance This is amongst a series of recently commissioned large-scale studies of their AI deployed in a real-world national health system environment supported by the NHS. The project will also provide a framework to establish which combination of studies works best to evaluate the AI.
The role holder will have the opportunity to undertake frontier research and produce publications in the novel design of evaluation studies for AI models in real-world health systems; as well as, be part of the frontier national work involving NHS, Alan Turing Institute, NICE, PHE, AAC and NHS X teams on how to safely and effectively integrate new, cutting edge AI technology, and establish the UK as a leading global exemplar for large scale deployment of AI solutions.
The research team will benefit from the support of a Turing Research Project Manager from within its strategic Health and Medical Sciences Programme.
Example Research Questions
The project will address a number of emerging questions in the development of AI solutions for clinical application. These could include and not exclusively:
- Defining multiple and potentially competing endpoint criteria when assessing the performance of AI healthcare solutions,
- Addressing issues of missing not-at-random data or uncertainty in ground truth labels in the retrospective use of data for performance assessment,
- Developing novel methods suitable for population-level datasets or Bayesian alternatives to classical testing,
- Devising a process by which to demonstrate generalisability of AI solutions.
The postholder will receive supervision and mentorship from academic, clinical and industry to address these types of issues within the Kheiron-Turing collaboration.
DUTIES AND AREAS OF RESPONSIBILITY
- Develop novel methodologies and studies to assess the safety and efficacy of Mammography Intelligent Assessment (Mia),
- Undertake frontier research in the novel design of evaluation studies for AI models in real-world health system
- To write or contribute to publications or disseminate research findings using other appropriate media
- Adhere to modern principles of reproducible and ethical data science in carrying out their responsibilities.
- To ensure compliance with secure handling of data and health and safety in all aspects of work.
- Drive collaboration with academic experts and broader research partners from across the Turing and the wider Turing / project community.
- Contribute to the broader research aims and challenges of the Health and Medical Sciences programme, and ensure positive feedback to the project partnership.
- Contribute to the life of the Institute and support its community
- A PhD (or equivalent experience and/or qualifications) in a relevant area which will include Mathematics, Statistics, Computer Science, or related discipline
- Substantial experience in statistical modelling
- Experience in performing data analysis on substantial real-world problems
- Significant experience of using a modern statistical programming language (such as R and Python)
- Ability to understand and apply the principles of reproducible data science in previous research
- Experience in working with modern artificial intelligence technologies
- Experience of developing and documenting analysis workflows for scientific research projects
- Demonstrate a level of scientific comprehension to allow in performing relevant literature reviews.
- Ability to critically evaluate experimental results and derive evidence-driven conclusions.
- Excellent written and verbal communication skills, including experience in the visual representation of quantitative data, documentation of software packages or data resources, the authoring of research papers or technical reports, and giving presentations or classes on technical subjects.
- Adapts the style of communication to the audience and ensures understanding.
- Ability to communicate complex, specialist or conceptual information clearly and persuasively, presenting compelling arguments to influence and/or negotiate satisfactory outcomes.
- Ability to lead own work Independently, and make independent decisions which are low risk and that mainly affect themselves or a small number of people and are guided by regulation and practice.
- Work with others to make collaborative decisions that may be operational or strategic and impact immediate team or work area.
- Recommend and advise on available options for decisions that affect operational processes, taking into account any risks.
- Uses judgement to analyse and solve problems, and take action to prevent recurrence of problems.
- Consider possible solutions to identify those which offer wider benefits, and obtain evidence to support thinking.
- Proactive approach to managing stakeholders and their requirements and identifying opportunities for collaboration
- Adapts services and systems to meet stakeholders’ needs and identifies ways of improving standards. Learns from issues and takes action to resolve them.
- Ability to plan and implement rigorous analysis plans.
- Identify and use a range of standard sources to gather and analyse routine data and produce reports that can be interpreted by others. Identify and use a range of standard sources to gather and analyse routine data and produce reports that can be interpreted by others.
- Understand when additional data is required and identifies appropriate sources. Produces reports that identify key issues and findings.
- Participates in networks within the organisation or externally to share knowledge and information in order develop practice or help others learn.
- Networks with others with shared interests, collaborating on projects and strengthening future relations.
- Working with confidential and sensitive data for research.
- Flexible attitude towards work
- Commitment to EDI principles and to the Organisation values
- Experience in the evaluation of predictive models in a clinical setting
- Research experience in biostatistical or clinical research studies
- Experience of regulatory processes involving software as medical devices
- Ability to act as an ambassador for the development and implementation of new AI regulatory evaluation processes.
If you are interested in this opportunity, please click the apply button below. You will need to register on the applicant portal and complete the application form including your CV, covering letter and contact details for your referees. If you have questions about the role or would like to apply using a different format, please contact them on 020 3862 3575, or email firstname.lastname@example.org.
CLOSING DATE FOR APPLICATIONS: 04 March 2021 at 23:59
TERMS AND CONDITIONS
This full-time post is offered on a fixed-term basis for two years. The annual salary is £36,000-£42,000 plus excellent benefits, including flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits
Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £32,000-£34,000 per annum.
EQUALITY, DIVERSITY AND INCLUSION
The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy and maternity, religion or belief, sex and sexual orientation.
Reasonable adjustments to the interview process will be made for any candidates with a disability.
Please note all offers of employment are subject to obtaining and retaining the right to work in the UK and satisfactory pre-employment security screening which includes a DBS Check.
Full details on the pre-employment screening process can be requested from HR@turing.ac.uk.