|Salary:||£32,236 to £39,609|
|Placed On:||4th December 2018|
|Closes:||7th January 2019|
This research position will investigate Bayesian uncertainty quantification tools for linear inverse problems across a range of scales. In the first instance this research will be primarily illustrated by computational imaging applications involving data under-sampling, high (non-standard) noise sources and observed phenomena which are non-stationary. While most existing uncertainty quantification tools simply measure image quality, it is often unclear how such measures translate into uncertainty about the information of interest, e.g., the presence or movement of an object or anomaly, as intended in this work. Typical application scenarios include hyperspectral imaging, low-photon imaging/ranging (single-photon Lidar) and radiation monitoring (nuclear safety).
The researcher will be supervised by Prof. Yves Wiaux in the Institute for Sensors, Signals and Systems along with Prof. Steve Mclaughlin and Dr Yoann Altmann. They will work closely with other UDRC researchers and interact regularly with our project partners in the UK Defence Science and Technology Laboratory (Dstl) and other industrial companies.
Key Duties and Responsibilities include:
This position is available for 30 months.
The successful candidate will have a good undergraduate degree and a PhD in Electrical Engineering, Applied Mathematics, Computer Science, Physics, or related discipline, with a focus on signal processing/ Data Science or closely related area.
For application details and further information please go to: www.hw.ac.uk/apply-jobs
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