PhD Studentship in Hardware Accelerators for Space Applications

University of Southampton School of Electronics and Computer Science

United Kingdom

PhD Studentship in Hardware Accelerators for Space Applications

Agents, Interactions & Complexity

Location: Highfield Campus
Closing Date: Friday 05 June 2020
Reference: 1263720FP

Supervisor: Themistoklis Prodromakis, Mark Zwolinski and Firman Simanjuntak

Project description

The aim of this PhD studentship is to develop radiation-hard AI hardware accelerators that can be used for delivering advanced computing capabilities in inaccessible and harsh environments (e.g. space). The project covers a wide spectrum of experimental research, including electron device characterisation, mixed-signal IC and/or embedded design, machine learning and neuromorphic engineering. These rad-hard AI accelerators can be used in a variety of applications ranging from satellite and (un)manned space missions to nuclear reactors and radiation detectors. 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.

Supervision:

  • Prof Themis Prodromakis – expert in AI Hardware.

  • Prof Mark Zwolinski – expert in IC Design & Hardware reliability.

  • Dr Firman Simanjuntak – expert in Failure analysis & Device Physics

The studentship is funded jointly by the UKRI MINDS CDT and DSTL. The DSTL Space programme will provide both expertise to support the research and offer a 3-month internship at the company.

Space Requirements

The prospect of developing low Size Weight & Power (SWAP), inherently radiation hard AI accelerators for satellites is highly appealing. Many current applications for satellites have high data transmission requirements and as satellites are being asked to do more, the ability to efficiently and ultimately autonomously decide what does and does not need transmitting to Earth will become more important. In space services this is specifically applicable with regards to Earth Observation (EO) and Satellite Communications (SATCOM). These 2 application areas are fertile areas for the exploitation of ‘on-chip’ satellite autonomy and should be pursued as end-goals, supported by the research in this project.

This project is funded through the UKRI MINDS Centre for Doctoral Training (www.mindscdt.ai). This is one of 16 PhD training centres in the UK with a unique focus on advancing AI techniques in the context of real-world engineered systems with a remit that spans novel hardware for AI, AI and machine learning, pervasive systems and IoT, and human-AI collaboration. We provide enhanced cross-disciplinary training in electronics and AI, entrepreneurship, responsible research and innovation, communication strategies, outreach and impact development as part of an integrated 4-year iPhD programme. 

The MINDS CDT is based in a dedicated laboratory on Highfield Campus at the University of Southampton. The lab provides a supportive environment for individual research, ideas sharing and collaboration, and the wider campus provides access to substantial high-performance computing (including dedicated GPU servers), maker and cleanroom facilities. You will take part in our annual, student-designed innovation camps, be able to work with industry and government partners through our internship scheme and be able to take part in exchanges with international university partners.

Funding: full tuition for EU/UK Students plus, for UK and EU students resident in the UK for previous 3 years, an enhanced stipend of £18,285, tax-free per annum for 4 years. years. 

Entry Requirements

Undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: 5 June 2020. 

How To Apply

Apply online , select the academic session 2020-21 “PhD MINDS” as the programme. Enter Hardware accelerators for space applications under the Topic or Field of Research.

Applications should include: 

Research Proposal

Curriculum Vitae

Two reference letters

Degree Transcripts


In your application, please refer to Polytechnicpositions.com

FACEBOOK
TWITTER
LINKEDIN

baner1

baner10

baner11

baner12

baner14

baner2

baner3

baner4

baner5

baner6

baner8

baner9