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Associate Research Engineer (Fixed Term)

Closing date: 
Sunday, 31 January 2021

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.

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science.

  • Supports and connects the growing data science research community 
  • Builds research capacity in data science to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Acts as a gateway for external organisations 

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