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AI Hardware for Symbol-level Processing


Project Description

Supervisor: Themis Prodromakis
Co-supervisor Alex Serb

Project description

The Centre for Electronics Frontiers at the University of Southampton is a dynamic interdisciplinary Centre that delivers novel solutions for advanced sensory systems, energy technologies and unconventional computing architectures. Our team encompasses diverse expertise ranging from materials process development to electronic devices, circuits and systems. This knowledge combined with our state-of-art facilities and strong collaborations with industry enables us to off¬er unique solutions to real-world problems.

Our ambition is to push the frontiers of electronics through emerging nanotechnologies, disrupting current ways of thinking by innovating advanced nano/bio-sensors, safe and efficient energy storage solutions and novel Hardware for AI. To realise this vision, we are seeking exceptional candidates to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The aim of this PhD studentship is to develop AI hardware accelerators that can be used for delivering computing capabilities beyond statistical learning, entailing computation at symbol-level. This involves treating data (already processed/classified via ANNs, CNNs, DNNs) as stable symbolic representations therefore allowing machines to reason and apply logic and common sense like humans do. This can be useful in a variety of real-time applications where AI systems are required to react when presented with unprecedented situations. The project covers a wide spectrum of experimental research, including machine learning, maths, and mixed-signal IC or embedded design. These novel AI hardware accelerators can be used in a variety of applications ranging from autonomous vehicles, smart assistance and robotic nurses. The PhD student will have the opportunity to join a multi-disciplinary team and to be trained and work in the world-class facilities of the Zepler Institute for Photonics and Nanoelectronics.

We welcome applications from candidates with a background in machine learning, electronics, maths and computer science. Prior experience with programming (Python, Tensor Flow), circuit design and artificial neural networks are highly desired.

Funding
Funded scholars will receive support for tuition fees, a bursary to cover living expenses (£18,000 tax-free per annum, up to 3.5 years) and a Research Training Support Grant for research consumables and conference attendance.

Please note funding available will normally support Home/EU students with standard research council restrictions. EU students are only eligible for a full studentship if they have lived, worked or studied within the UK for 3 years prior to the funding commencing. We will consider applications from exceptional candidates not meeting these criteria.

More information on the Centre for Electronics Frontiers can be accessed at: https://cef.soton.ac.uk


Entry Requirements
MEng/MSc (or equivalent, or near completion) with first class honours or distinction in Engineering, Physics, or a closely related subject.

EU/Overseas applicants should achieve an IELTS score of 6.5 with at least 6.0 in each competency. Click here for information.

Closing date: applications should be received no later than 31 August 2020 for standard admissions, but later applications may be considered.

How To Apply

Applications should be made online here selecting “PhD Nanoelectronics (Full time)” as the programme. Please enter Centre for Electronics Frontiers under the Topic or Field of Research.

Applications should include:
Curriculum Vitae
Two reference letters
Degree Transcripts to date
Apply online: https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page

For further information please contact:

How good is research at University of Southampton in General Engineering?

FTE Category A staff submitted: 192.23

Research output data provided by the Research Excellence Framework (REF)

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