Job description

An excellent opportunity has presented itself at GOSH Data Research, Innovation and Virtual Environments (DRIVE) for a Machine Learning Engineer position. GOSH is at the forefront of using new and innovative technologies in the clinical treatment of patients and a Research and Innovation Platform is seen as essential to support the Trust’s role nationally and internationally as a Biomedical Research Centre. The Trust has implemented and deployed the Aridhia Research and Innovation Platform (research platform) to provide a rich source of data for audit, research and operations and allow us to keep pace with our peers regarding recruitment to clinical trials. The research platform forms the core of the Trust’s Digital Research Environment (DRE), which alongside other systems and technical infrastructure will enable GOSH to capitalise on developments such as artificial intelligence and advanced clinical decision support, underpinning research studies and improving Trust operational processes for many years to come.

The Machine Learning Engineer will join the team to assist in the development of NLP and ML capabilities. The overall aim of this role is to be a critical link in getting innovative data-based tools and technologies, that have the potential to improve the lives and outcomes of GOSH patients, into the hands of our clinical teams. We are seeking a team player with a flexible approach to work who wishes to join us at this truly exciting time as we embark on the next phase of GOSH’s ambitious digital transformation programme.

The successful candidate will work closely with data science, NLP and data engineering teams and develop solutions by adopting some of the best practices of software development lifecycle, Reproducible Analytics Pipelines (RAP). The projects will involve a range of technical and usability challenges including imaging data.

We are therefore seeking for a candidate who is keen to work on contributing towards continual development of NLP and ML related workstreams and has excellent technical skills to develop computer vision and machine learning tools but also interested in working with clinical teams to understand how the tools can be created to fit within their existing workflows and provide information to them in an engaging way.

This is a fantastic opportunity to join our friendly and welcoming team with its great diversity of skills and experience, we look forward to receiving your application.

GOSH is committed to recruiting the best person for the job, based solely on their ability and individual merit as measured against the criteria for the role; through a process that is fair, open, consistent and free from bias and discrimination.

We are committed to being a diverse and inclusive employer and foster a culture where all staff are valued, respected and acknowledged. All applicants will receive consideration for employment without regard to race, colour, national origin, religion, sexual orientation, gender, gender identity, age, disability status or length of time spent unemployed.

We particularly welcome applications from BAME communities, people with disabilities and/or long-term health conditions and LGBT+ community members.

We have policies and procedures in place to ensure that all applicants and employees are treated fairly and consistently. We are proud to be accredited as a Disability Confident Employer, a member of Business Disability Forum and a Stonewall Diversity Champion.

We have active and Executive supported BAME, LGBT+ and Allies, Disability and Long-Term Health Conditions and Women’s staff networks. Staff networks are employee-led groups formed around interests, issues and a common bond or background. Staff network members create a positive and inclusive work environment at Great Ormond Street Hospital by actively contributing to the Trust’s mission, values and efforts specific to inclusion. All of our staff networks are open to any employee.

For further details / informal visits contact: Name: Pavithra Rajendran Job title: Senior Data Scientist Email address:

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