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Edinburgh, United Kingdom The University of Edinburgh Full timeSummary: Applications are invited for a 4-year PhD studentship within the new established EPSRC funded Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS). The program involves both a PhD research project and integrated studies as part of a cohort of like-minded students. The integrated studies will include advanced...
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PhD Studentship
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Edinburgh, United Kingdom The University of Edinburgh Full timeSummary: This research proposal addresses challenges in the UK's construction industry, focusing on sustainability & safety. It aims to develop machine learning models that combine data from similar infrastructure and integrate information from previous inspections to predict potential problems. The models will also account for the impact of changing climate...
PhD Studentship
4 months ago
Sensor networks, sensor fusion and management techniques address key challenges in intelligence, surveillance, target acquisition, and reconnaissance (ISTAR). Opportunities in adaptive data-driven sensor tasking and resource management include adaptive sensor placement, adaptive waveform design to reflect the target reflection characteristics and channel environments, and adaptive sensor selection. Although these problems have solutions in specific use cases, this theme will consider scenarios with broader applications involving multiple heterogeneous sensors on single or multiple cooperative autonomous airborne platforms.
The solutions developed in this should be robust to dynamic and congested environments, adverse weather conditions, and mutual sensor interference. A range of algorithmic and signal processing or machine learning technologies will be considered, as well as specific technical challenges. For example, projects in this theme will consider aspects related to:
wide area motion imaging (WAMI),position, navigation, and timing issues (PNT); robustness to adversarial attack; sensor fusion and tracking applications; use of kernel and Monte Carlo methods; outlier-robust (and other metrics) messages in belief propagation algorithms; and scheduling in large dynamic networks. Probabilistic and Bayesian frameworks will be preferred to enable uncertainty quantification and management.
The techniques, solutions, and challenges proposed in this theme has applications across a range of defence and civilian applications, including search and rescue, law enforcement, and remote sensing.
This project will be jointly supervised by:
Prof James Hopgood,
Prof Mike Davies,
Please note that this advert will close as soon as a suitable candidate is found.
Eligibility:
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Please note that as this is a defence based project, only UK/EU students are eligible to apply. International applicants are not eligible.
Further information on English language requirements for EU/Overseas applicants.
Funding:
Tuition fees + stipend are available for applicants who qualify as:
- a UK applicant
- an EU applicant (International/non EU students are not eligible)
Funding is available through EPSRC Prosperity Partnership Programme. As this is a defence related project there are nationality restrictions (see above).
Informal Enquiries:
Prof James Hopgood,
Further Information:
The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here:
Tuition fees + stipend are available for applicants who qualify as a UK applicant or an EU applicant (International/non EU students are not eligible)
