Fixed-term: The funds for this post are available for 2 months in the first instance.
This position is funded by the EPSRC Global Challenge Research Fund 'AirborNet: Data-Driven Modelling for Airborne Diseases'. 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 cluster computing environment, where Unikernels are exploited to improve data processing performance. The project includes development of CO2 sensing unit with Raspberry Pi. Ideal candidates will hold a BSc in a Computer Science related field. Following skills are essential.
- C, C++ programming
- Raspberry Pi
- Network communication
Basic of Machine Learning
Also the following experiences will be desirable:
Writing applications using Deep Neural Networks, Convolutional Networks
- CUDA on GPU
- Unikernel (e.g. rumprun, mirage)
The post is intended to start on the 8th January, 2018, although some flexibility is possible. Please email informal enquires to Dr. Eiko Yoneki (email: firstname.lastname@example.org).
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
You will need to upload a full Curriculum Vitae (CV) and 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 NR14083 on your application and in any correspondence about this vacancy.
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