EPSRC Industrial CASE PhD Studentship in Machine Learning for Adaptive Risk Management in Cyber-Physical Systems

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Job Description

Scholarship: A full-time EPSRC Industrial CASE PhD research studentship, including full stipend and tuition fee costs, in machine learning for the safety and security of cyber-physical systems, IoT and Sensor Networks is available for 4 years starting January 2021 (or shortly thereafter). EPSRC Industrial CASE Awards are flagship collaboration projects between industry (IBM in this instance) and academia, aiming to create the research scientists of tomorrow and deliver real value to all stakeholders.

Research theme: Increasingly Industrial Wireless Sensor Systems are being used to support Smart Infrastructures in real-time with little human input. This PhD studentship, with the Adaptive Emergent Systems Engineering Group and IBM UK, is concerned with using Deep Learning to create heterogeneous and distributed Machine Learning components to support smart infrastructures, where robustness and resilience are key to provide their continuous operation. The successful student will contribute to the Machine learning fields as well as to Cyber-Physical Systems


The studentship will commence in January 2020 and will be available for up to four years, with a stipend equivalent to UKRI rates (approx. £17,285 tax free for 2020/21 and subject to change for future years), plus an industrial top-up stipend, subject to contract. This also covers full university tuition fees (at Home level), and travel support for fieldwork, conferences and industrial visits

Job Requirements

To apply for this position, you will need to have a strong background in at least two of the following areas: machine learning, control systems, embedded systems, wireless networking, and AI.

Applicants are expected to have a First Class or Distinction Masters level degree, or equivalent, in a relevant scientific or technical discipline, such as computer science or mathematics. Applicants must be fluent in spoken and written English.

How To Apply

Please forward your CV to Teresa Ng tng@imperial.ac.uk
Early applications are encouraged. Informal inquiries about this position are also encouraged and can be directed to Professor Julie McCann. For further information see https://wp.doc.ic.ac.uk/aese/
Applicants are advised to visit http://www.imperial.ac.uk/computing/prospective-students/courses/phd/ for general information on becoming a PhD student in the Department of Computing.
We are committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people.

Closing Date: 30th November 2020

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