The next generation of domestic robots will mark a revolutionary change in capability. Current mass market, home based robots are restricted to vacuuming on a single floor level. The latest variants perform this role very effectively, but customer expectations are for much greater functionality. This will be enabled by the evolution of high fidelity 3-d sensing, anthropomorphic actuation suited for domestic environments, scene semantics provided by artificial intelligence, and ever massively-increased embedded processing power. Evidently, we have constituent components which should fuel game-changing domestic robots in the next few years.
A critically important challenge in realising this potential, that forms the focus for this PhD project, is concerned with the higher level (on robot) processing requirements. The research will investigate distributed and heterogeneous hardware architectures capable to deliver the necessary performance including CPU, GPUs, Intelligent Processing Units (IPUs), dedicated hardware functions, reconfigurable elements, on-chip networks and memory systems. The outcome of the project will be insights into the architecture of System-on-Chip devices to support the next generation of domestic robots.
An ideal candidate for this project should be excited about research spanning multiple layers of the robotic systems stack, and have experience in at least some of the following topics: computer architecture (including accelerators), re-configurable microelectronics and robotic/image processing algorithms.
The collaboration between Imperial College London and Dyson will provide a unique opportunity for performing leading edge research that will have a direct conduit to next generation domestic robots!
The PhD student will be jointly supervised by Dr Christos-Savvas Bouganis (Imperial College), Prof. Paul Kelly (Imperial College) and Dr. Rob Deaves (Dyson).
A competitive candidate for this role should demonstrate the following:
· A good First-Class Degree (or International equivalent), in electronics or computer science
· A Masters level degree qualification and/or relevant experience.
Experience and skills:
· Software development for deep learning
· Computer arithmetic
· Programming embedded systems
· FPGA circuit design
· Probabilistic machine learning
A lack of experience in the above experience and skills could be compensated by evidence of research potential.
For queries regarding academic or technical skills for the project, you may contact Dr. Bouganis (email@example.com).
Please click here to apply. Course code: Electrical Engineering Research – H6ZX
NB: In the application, the proposed research supervisor should be “Dr Christos-Savvas Bouganis” to indicate that the application is for this post.
Any queries regarding the application process should be directed to Miss Lina Brazinskaite firstname.lastname@example.org
Closing Date: Applications are considered across the year till the position is filled.
Imperial College London is the UK’s only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.
Additional information on the PhD programme in the Department of Electrical and Electronic Engineering can be found here.
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