Our aim is to tackle the challenges of evolving pervasive applications such as:
- Internet of Things
- Autonomous Devices
- Bio-implantable Microsystems
Expertise in the Group includes:
- circuits, architectures, algorithms, and systems
- design automation tools
- designing systems with low to zero energy footprints
- converting energy to computation
- communication with maximum energy utilization in a wide band of operating conditions
The group is made up of seven academic staff, seven research associates and 30 PhD students. The expertise of the Group covers fundamental and applied research in complex microsystems engineering.
The group has been very successful in producing high quality PhD graduates, most of whom go on to successful academic and industrial careers, in the UK, Europe, Asia and the Americas. The area of µSystems has been experiencing continuous world-wide growth and the skill set required for obtaining a PhD degree in it, which our programme provides, is extremely useful not only for people who intend to develop a further career within the microelectronics discipline but also elsewhere.
Some of our PhD graduates are currently holding senior positions in diverse fields from computing science to rail transport systems.
By the end of the programme you would have made contributions to and attended high quality international conferences. You would have also had experiences of collaboration with colleagues and external experts, and published papers in recognized research journals.
The group has a highly connected environment and friendly atmosphere. Students on different projects frequently interact with one another both formally through our regular seminars such as the ASL series, co-hosted with colleagues in the School of Computing Science, and informally through daily contacts in the office and recreation spaces around the school.
Our students include mathematicians, programmers, circuit designers, biologists, and others from diverse backgrounds.
Available PhDsAvailable PhDs
Currently, the group is seeking to recruit PhD candidates in the following areas:
Energy and Power in Computing
Computing systems, especially hardware, are becoming more and more energy and power constrained. Students will investigate the relationship between energy and power on the one hand and computation on the other. Sup-topics include energy modulated computing, low power electronics, and energy harvesting, storage and distribution on chip.
Asynchronous Circuits and Systems
Asynchronous techniques, by not relying on a consistent global clock, offer solutions to many of the current and future problems encountered in computing. Students will explore and develop novel solutions for the modelling, analyses, synthesis and design of asynchronous circuits and systems. There are scopes for students to work at all levels of abstraction from theoretical studies and algorithmic development to the designs of specific circuit elements.
On-Chip Fine-Grain Control
Computing systems are increasingly limited by the utilization wall, which forces the use of dynamic feedback control at the smallest granularity, i.e. on-chip circuits. Students will investigate issues related to building on-chip dynamic control of computation in relation to variations in the environment and the circuits. Successful outcomes include novel control algorithms, control data communication solutions, and the hardware of these solutions.
On-Chip Parametric Sensing
To control computation dynamically on-chip requires the sensing of physical parameters related to the environment and circuit conditions. On-chip sensing of these parameters is non-trivial because reliable references are usually missing and the sensors themselves are based on the same kind of circuit as the system. Students will develop novel sensing techniques to overcome these problems.
Current system-level strategies to deal with power variability in the environment is through a multi-modal paradigm, for instance, a laptop may have a number of operating modes such as mains plugged in, on battery with networking, low activity, sleep, etc. Students will work at the lowest hardware level to develop an entirely new paradigm based on multiple layers of circuits and functions targeting the ultimate survivability of computation.
Microelectronic systems are increasingly used in applications where security and privacy are seen as key. As semiconductor technology moves into the nanoscale range, variability increases and the properties of hardware-level security change with it, including possible uses and nature of attacks. Students will investigate various aspects of nanoscale security due to variability; specifically, its theoretical foundations; attacks and countermeasures; and approaches that can harness the effects of variability for designed-in security (i.e., security-enabling technologies for use in silicon chips).
Biomedical systems such as heart pacemakers and visual prosthesis require advanced electronic processing architectures. Students will develop digital/analogue FPGA/CMOS designs to mimic key computational centres in the eye and brain. Successful outcomes will be translated to retinal and visual prostheses.
This is an opportunity to work on implantable optoelectronic neural stimulators and sensors. Students will explore implantable structures which link micro-optoelectronics stimulator and sensing systems. Real time close loop systems connecting biosensor inputs and neural stimulation will have particular application to brain prostheses, motor neurone disease and visual prosthesis.
These areas are examples only and non-exclusive. Candidates are urged to contact the group's academics for other possibilities.
In addition to the CASE studentship, the group regularly provides financial support to its PhD students on a case-by-case basis and opportunities to work within our current research projects with external (e.g. EPSRC) funding.
Contact the leader of µSystems Professor Alex Yakovlev for further details.
Eligibility criteriaEligibility criteria
You should have at least a 2:1 honours degree (ideally a first class degree), or a combination of qualifications and/or experience equivalent to that level in a relevant discipline (typically in computer science, engineering, mathematics or in the physical sciences).