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Department of Applied Mathematics and Theoretical Physics

We are looking for an accomplished Machine Learning Engineer to join the newly established Cambridge Centre for AI in Medicine (CCAIM) at the University of Cambridge. CCAIM is a multidisciplinary centre created to produce cutting-edge machine learning (ML) research to solve complex problems in biomedical science, medical discovery and healthcare delivery. Funded by AstraZeneca and GSK - and with strong research ties to the NHS - CCAIM will also drive the revolution in ML-powered precision medicine.

The position is available to start as soon as possible and would be offered as a five-year fixed-term contract in the first instance.

The Machine Learning Engineer will be responsible for designing and building bespoke software packages for the Centre's groundbreaking algorithms, models, and techniques by working closely with researchers to bring recently published methods into a unified and publicly available framework. Projects will be novel, diverse, challenging, and impactful, with examples ranging from designing software to preserve the privacy of patient data to building an end-to-end automated machine learning pipeline to aid clinical decision support.

Given the exploratory nature of the research in question, this role will appeal to anyone who welcomes the chance to solve engineering challenges that have yet to be formulated, let alone attempted. There will be substantial scope for creative development work.

The successful candidate will hold a BSc or MSc in Computer Science or an equivalent discipline, and will have a thorough understanding of mathematics, probability, statistics, algorithms, data structures, software architecture and design. They will be highly proficient in Python, and have considerable experience with autodiff frameworks (Tensorflow, PyTorch, JAX) and data/numeric libraries (numpy, pandas, sklearn, keras). Experience with software at scale and contribution to open source projects will be considered very favourably. Required competencies include strong project management, ability to work constructively with colleagues from a variety of international backgrounds, and a clear aptitude for translating theoretical work into real-world application.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please provide a CV and covering letter. Candidates must provide the names and contact details of two referees who are familiar with their work in the relevant field whom we can contact for a reference before the interviews, which are expected to take place soon after the closing date.

Please quote reference LE26745 on your application and in any correspondence about this vacancy.

Informal enquiries about the position may be made to the coordinator for this recruitment at:

The University values diversity and is committed to equality of opportunity. The Department would particularly welcome applications from women as we have an historic imbalance in the number of women holding positions at this level.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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Closing date

Jun 21st 2021

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