Research Associate in Embedded AI for the IoT

The role

We are looking for an enthusiastic, self-motivated individual to contribute to the EPSRC-funded, CHARIOT project on Cyber Security for severely resource-constrained industrial IoT systems. CHARIOT is devising, design, prototype, and evaluate creative, cutting-edge solutions for the detection of, prevention of, recovery and immunisation from ransomware attacks in industrial IoT environments.

Research outcomes and artifacts will be made available to industry professionals and the IoT security research community, to benefit from our findings and to foster collaboration towards creating more secure IoT and cyber-physical ecosystems.

The project is a collaboration with the University of Kent and is directly supported by industry partners. The project is aligned with the aim and objectives of the Research Institute in Trustworthy Interconnected Cyber-physical Systems (RITICS).

You will contribute to an ambitious research programme to prevent, detect, counter, and recover from ransomware attacks on IIoT systems. You will integrate artificial intelligence approaches with resource constrained edge/IoT devices.

What will you be doing?

Over the course of the project, you will be:

• Devising, prototyping and evaluating innovative detection and countermeasures against ransomware attacks in industrial IoT systems.
• Leading and contributing to the authoring of journal and international conference
publications.
• Assisting with general project administration duties, such as the authoring of verbal and written reports and project presentations.
• Representing the University of Bristol in project meetings, presenting your work, taking feedback and developing your individual research directions.
• Creating and maintaining technical documentation.
• Working towards developing your own career in higher education by co-supervising students at various stages of their studies (e.g. final-year undergraduates, MSc).

You should apply if

You are excited about undertaking high technology readiness, applied research.

• You will have a track record on applying machine learning techniques to address new research challenges (ideally with track record in distributed/federated AI or embedded neural networks).
•You have a track record in one or more of the following areas:
o Low-power communications and networking for battery-powered, severely constrained wireless embedded devices.
o Systems and/or Network Security.
• You understand the nature and complexities of developing working prototypes of research ideas.
• You have strong software and firmware development skills using Python or C.
• You have prior experience with working with, or in industry.
• You enjoy being member of a large team of engineers and researchers.
• You can build strong, effective relationships with a range of people from different sectors and levels of seniority.
• You have excellent communication skills and can clearly articulate verbally and in writing.

Additional information

For informal queries, please contact: James Pope - Senior Lecturer (james.pope@bristol.ac.uk)

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