Research Assistants / Associate in Computer Science

University of Cambridge

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 2 years, with the possibility of extension as grant funds permit. Appointment to Senior Research Associate will be considered for exceptional candidates.

We are seeking one or more Research Assistants (without PhD) or Research Associates (holding or soon to obtain a PhD) to support a number of overlapping research projects applying machine learning and related techniques to Internet of Things data management and security, edge computing and orchestration, and 5G networking. The work will involve working with other researchers and PhD students to design and implement networked systems addressing challenges in those areas, and evaluating those systems through simulation and deployment.

Successful candidates will hold, or shortly complete, a Ph.D. in Computer Science, or have equivalent skills and experience through non-academic routes, and must be able to evidence:

  • Ability to communicate clearly in English, in both written and spoken forms, whether through an academic publication record commensurate with level of experience, or through other less formally published examples of rigorous technical writing.

  • Experience of or aptitude for rigorous system measurement and evaluation, including experiment design, data capture, and data analysis. This may have been gained in commercial or industrial settings as well as through production of academic papers.

Desirable areas of experience or aptitudes for your application to evidence include:

  • Systems-level (e.g., OS kernel, device driver, assembly level) development.

  • Core Internet protocols (e.g., TCP/IP, UDP, DNS), the BSD Socket APIs, and Linux software development.

  • Application of machine learning and related techniques to practical problems.

  • Consensus systems such as Paxos or Raft.

These posts will be based in the Systems Research Group which provides a supportive and rigorous environment in which to undertake world-leading research in a wide range of topics in computer systems. The group's outputs are not limited to publications but often also include spin out companies -- significant successes include XenSource (acquired by Citrix Systems Inc. for $500M in 2007) and Unikernel Systems (acquired in 2016 by Docker Inc.).

Questions about the post may be addressed to Prof. Richard Mortier Please quote reference NR24252 on your application and in any correspondence about this vacancy. We welcome applications from candidates with experience outside academia.

These posts will require active engagement with research collaborators and sponsors, initially online but, as the COVID-19 crisis abates, this will also involve domestic and international travel. Applicants may be able to begin work remotely, due to COVID-19, but should contact the department to confirm potential applicability and anticipated arrangements. It is expected that successful candidates will work on-site in Cambridge in due course.

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

Please provide a Curriculum Vitae (including publication list and details of at least two references), alongside a brief statement of the contributions you would make to any of the project areas listed above, drawing attention to relevant experience with systems, networking and/or machine learning, as a single combined PDF. If you upload any additional documents which haven't been requested, we will not be able to consider these as part of your application.

Please quote reference NR24252 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.

Apply online