We seek an exceptional individual with a strong theoretical background who is interested in both understanding and contributing to fundamental problems in machine learning and evaluating and demonstrating their utility in the context of digital health and AMR. The post holder must have an outstanding track record in creative, original independent research of the highest impact, the ability to work with a wide range of stakeholders in the UK and internationally, and the ability to multi-task, and organise their work to meet deadlines. This role will be funded until 31st May 2027 in the first instance. Research Fellows – 'Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £39,148 – £41,833 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.' This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff.
The successful candidate is expected to conduct research on machine learning tasks that relate to machine learning models to reduce the risk of AMR, particularly with respect to surveillance and stewardship. The post holder will have a strong theoretical knowledge of machine learning; experience of (time series) disease modelling would be beneficial but not essential. Actively engage with the research groups of both Prof. Cox and Wang; Publish research outcomes to either top-tier computer science conferences and/or interdisciplinary journals.
The UCL Ways of Working supports colleagues to be successful and happy at UCL through sharing expectations around how we work. As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:
As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; and LGBTQI+ people. Our division holds an Athena SWAN Silver award, in recognition of our commitment to advancing gender equality.
Tagged as: Life Sciences
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