Research Assistant/Associate in Parallel Processing using Raspeberry Pi

University of Cambridge - Department of Computer Science and Technology

West Cambridge

Research Assistant £25,728 - £29,799 or Research Associate £29,799 - £38,833

Fixed-term: The funds for this post are available for 3 months.

This position is funded by the EPSRC Project 'FRuIT: Federated Raspberry Pi Micro-Infrastructure'. The successful candidates will join the systems research group. The project deals with distributed data processing over Raspberry Pi and other single board (e.g. NVIDIA Jetson X2) based computing environment, where Unikernels are exploited to improve data processing performance. The project includes development of various sensing units with Raspberry Pi also LoRaWAN. The target applications are machine learning based image classification, environment recognition. Ideal candidates will hold a BSc in Computer Science or a related field.

The following skills are essential:

  • C, C++ programming
  • Raspberry Pi
  • TensorFlow/PyTorch
  • Linux
  • Network communication
  • Basic of Machine Learning

The following experience will be desirable:

  • Writing applications using Deep Neural Networks, Convolutional Networks
  • CUDA on GPU
  • Unikernel (e.g. rumprun, mirage)

This position can be filled by an appropriate candidate at research assistant or research associate level, depending on relevant qualifications and experience. Appointment at research associate level is dependent on having a PhD (or equivalent experience). Where a PhD has yet to be awarded appointment will initially be made as a research assistant and amended to research associate when the PhD is awarded.

The post is intended to start in May 2018, although some flexibility is possible.

Please email informal enquires to Dr. Eiko Yoneki (email: eiko.yoneki@cl.cam.ac.uk).

To apply online for this vacancy and to view further information about the role, please visit:

www.jobs.cam.ac.uk/job/17086. This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form.

Please ensure you upload your Curriculum Vitae (CV) and a covering letter. 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 NR15182 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

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

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