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Research Assistant/Associate/SRA in Machine Learning Systems (Fixed Term)
  • Python
  • Java
  • Linux
  • Machine Learning
  • NumPy
  • Azure
  • PyTorch
University of Cambridge
Cambridge
113 days ago

Research Assistant £26,715-£30,942 or Research Associate £32,816-£40,322 or Senior Research Associate £41,526-£52,559

Fixed-term: The funds for this post are available for 18 months in the first instance.

Role Summary

We are seeking an independent detail-oriented individual with strong hands-on systems skills, and familiarity with machine learning (or willingness to learn), to participate in projects within an active research team of PhD students and other RAs (see team description below). The core of this role will be two-fold. First, to administer and maintain existing experimental systems and code already developed by the team. Second, to participate in projects with other team members that require a mix of machine learning and systems - in which this role will aim to contribute primarily with system research and engineering. Opportunities to publish in top-tier venues and mentor PhD students will exist, depending on the experience of the successful candidate. This role will also focus on open-sourcing and maintaining select outcomes of research.

Projects engaged by this role are expected to change from time to time, but upon joining this role will participate within the following:

(1) Open-Source Federated Learning Platform for Embedded/Mobile Platforms

(2) On-board Machine Learning for Satellites

Research Lab: Machine Learning Systems

Successful candidates for this position will join our active research lab led by Nicholas Lane and 12 other PhD students and RAs. We investigate a variety of open problems that sit at the intersection of machine learning and various forms of computational systems (viz. embedded, cloud, mobile). The scientific contributions of our lab often take one of two forms. First, the development of novel algorithmic and theoretically principled machine learning methods - especially those with applications to the modelling of data such as image, audio, spatial and inertial information. Second, the design and architecture of system software that treat machine learning computation as a first-class citizen - this often results in transformative increases in training and inference efficiency. Our unifying aim is to invent the next-generation of device- and cloud-based systems able to perceive, reason and react to complex real-world environments and users with high levels of precision and efficiency. We seek to achieve this impact through holistic full-stack approaches that encourage lab members with skills in algorithms, hardware, statistics, mathematics and software to work closely together to solve critical challenges in this area.

Please refer to the further particulars for more detailed information.

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

Essential Qualifications

  • BSc/BEng in computer science/software engineering/physics or similar
  • Strong programming experience in Python
  • Good understanding of distributed systems and operating systems
  • Basic understanding of machine learning and related libraries/frameworks such as NumPy, TensorFlow, and/or PyTorch
  • Basic understanding of embedded systems development
  • Good understanding of test-driven development and continuous integration
  • Basic grasp of common Linux command line tools

Beneficial Qualifications

  • MSc/MEng or PhD in computer science/software engineering/physics
  • Experience in conducting research and publishing academic papers in top-tier research venues
  • Experience with GPUs environments and systems for machine learning
  • Experience with FPGAs and/or non-trivial embedded system development
  • Experience in mobile programming (Kotlin/Java on Android, Swift/Objective-C on iOS)
  • Experience in cloud environments (AWS, Azure, GCP)
  • Understanding of common packaging formats (e.g., Python Wheels, Docker)
  • Prior experience with gRPC/ProtoBuf

For informal enquiries, please contact Dr Nic Lane: ndl32@cam.ac.uk.

Appointment at Research Associate level is dependent on having a PhD or a combination of Masters degree along with considerable experience. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded. For appointment at Senior Research Associate level, the successful candidate will have to show evidence of multiple and extensive experience of the above qualifications.

You will need to upload a full curriculum vitae (CV) and a 1-page covering letter outlining your relevant past experience, and include the contact details for 3 referees. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please quote reference NR23353 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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

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