PhD Studentship, AI Hardware for Symbol-Level Processing
Centre for Electronics Frontiers
Location: Highfield Campus
Closing Date: Tuesday 31 August 2021
Supervisory Team: Alexander Serb, Themistoklis Prodromakis, Wendy Hall
The aim of this PhD studentship is to develop AI hardware accelerators that operate beyond statistical learning, by computing at the symbol-level. This involves treating data (already processed/classified via ANNs, CNNs, DNNs) as stable symbolic representations in order to allow 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.
The Centre for Electronics Frontiers
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 offer 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.
If you wish to discuss any details of the project informally, please contact Dr Alex Serb, Centre for Electronics Frontiers, Email: A.Serb@soton.ac.uk.
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent) or an MEng/MSc (or equivalent, or near completion) with first class honours or distinction in Electronics, Engineering, Machine learning, Computer Science or a closely related subject.
Closing date: applications should be received no later than 31 August 2021 for standard admissions, but later applications may be considered depending on the funds remaining in place.
Funding: For UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years.
How To Apply
Applications should be made online. Select programme type (Research), 2021/22, Faculty of Physical Sciences and Engineering, next page select “PhD Nanoelectronics (Full time
Applications should include:
- Research Proposal
- Curriculum Vitae
- Two reference letters
- Degree Transcripts to date
For further information please contact: firstname.lastname@example.org