Qualification Type: | PhD |
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Location: | Edinburgh |
Funding for: | UK Students, EU Students, International Students |
Funding amount: | annual stipend of £20,716 tax-free |
Hours: | Full Time |
Placed On: | 1st May 2024 |
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Closes: | 2nd June 2024 |
Position location, which in general comprises Direction of Arrival (DOA) and Time of Arrival (TOA) estimation, is an important area of research in many applications, including Radar signal processing and Fifth Generation (5G) and Sixth Generation (6G) commercial wireless systems. Conventionally this has been performed using either relatively simple algorithms based on received signal power measurement or more sophisticated subspace techniques, such as MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance techniques (ESPRIT). Recently, the implementation of position location estimation using Machine Learning (ML) techniques has been proposed as a methodology to improve performance beyond that of existing techniques, particularly in non-line-of-sight signal propagation conditions which occur commonly in many applications. This is an active area of research and is showing significant promise.
The project is sponsored by the company AMD and will involve close industrial collaboration to develop and test novel machine learning algorithms for position location. Following an initial literature review to define the state of the art, the following main research phases are expected:
It is likely that the specific objectives of the project will evolve throughout the PhD. However, AMD believes that it is important that the project comprises both theoretical study of the candidate techniques and practical implementation on AMD hardware.
Eligibility:
An undergraduate degree in Electronics and Electrical Engineering, Computer Science, Physics or related discipline.
Applicants who require an ATAS certificate to work study in the UK will not be eligible for this PhD programme. A list of nationalities can be found here: www.gov.uk/guidance/find-out-if-you-require-an-atas-certificate
Further information on English language requirements for EU/Overseas applicants: edin.ac/2NThGAe
Further Information
This project will run as part of the research council funded Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS) - spads.ac.uk. This is a four year programme involving both a PhD research project and integrated studies as part of a cohort of like-minded students.
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: www.ed.ac.uk/equality-diversity
Funding notes
A successful candidate will receive an enhanced annual stipend of £20,716 tax-free, which increases annually.
Tuition fees + stipend are available for applicants who qualify as Home applicants. Applications will be considered from EU/International Students who meet the eligibility requirements.
To qualify as a Home student, you must fulfil one of the following criteria:
Further information and other funding options: edin.ac/3Upu0qt
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