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Department of Applied Mathematics and Theoretical Physics

The University's van der Schaar Lab, which ranks among the world's most recognized research groups in the domain of machine learning for healthcare, currently has one opening for an Associate Research Engineer. With a start date on or before end of March 2021, the position will be offered as a two year fixed term contract in the first instance.

Sitting within the University's Department of Applied Mathematics and Theoretical Physics, Wilberforce Road, Cambridge, CB3 0WA, the van der Schaar Lab's mission is to create cutting-edge machine learning methods and apply them to drive a revolution in healthcare. Its research spans an extremely diverse range of sub-fields within machine learning, including deep learning, causal inference, Automated ML, transfer learning, reinforcement learning, ensemble learning, and interpretability. The Lab's projects are designed with clinical application in mind, and have already been successfully implemented in real-world settings for screening, prognosis, time-to-event analysis, predictive resource allocation and more.

Led by Professor Mihaela van der Schaar, the Lab benefits from international interest and support from both prominent public-sector research groups (National Science Foundation, Office of Naval Research, etc.) and leading multinational companies in the insurance (Aviva), pharmaceuticals (AstraZeneca, GlaxoSmithKline) and tech (Microsoft Research) sectors. The Lab is extraordinarily well-represented at leading global machine learning conferences, having presented a combined total of 22 papers (as well as numerous keynotes and tutorials) at NeurIPS, ICML, ICLR and AISTATS within the last year.

The Associate Research Engineer will be responsible for designing and building bespoke software packages for the Lab'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.

Fixed-term: The funds for this post are available for 2 years in the first instance.

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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 in early February 2021.

Please quote reference LE25098 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 research staff positions.

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

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

Jan 31st 2021

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