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Combinatorial Artificial Intelligence for Defence Applications PhD - Sponsored by BAE Systems

Cranfield University

Qualification Type: PhD
Location: Bedford
Funding for: UK Students, EU Students
Funding amount: £19,237 + £7,500 top-up (tax free) plus home fees* for four years
Hours: Full Time
Placed On: 14th October 2024
Closes: 5th March 2025

Funding for: UK

Funding amount: Sponsored by EPSRC, BAE Systems and Cranfield University, this iCASE studentship will provide a bursary of up to £19,237 + £7,500 top-up (tax free) plus home fees* for four years

Supervisors: Professor Weisi Guo 

Fully funded Ph.D. opportunity in Aerospace AI. Sponsored by EPSRC and BAE Systems covering tuition, fees and a bursary of up to £19,569 (tax free) + £7,500 industrial top-up. Combinatory Artificial Intelligence (also known as Third Wave AI as initially described by DARPA) is the term that references the next foreseen advances within Artificial Intelligence. This stems from the two main styles of AI development over the last two decades. This research topic aims to define novel approaches to developing and combining these intelligences, utilising both 1st and 2nd wave AI approaches, in the context of Defence applications.

Combinatory Artificial Intelligence (also known as Third Wave AI as initially described by DARPA) is the term that references the next foreseen advances within Artificial Intelligence. This stems from the two main styles of AI development over the last two decades.

This Ph.D. research aims to define novel approaches to developing and combining these intelligences, utilising both 1st and 2nd wave AI approaches, in the context of Defence applications. Such applications are expected to include:

  • Robust and “functionally explainable” machine-aided decision support for Safety and Mission Critical objectives e.g. fault detection/tracing, evasive manoeuvring, target selection etc.
  • Detailed semantic understanding of operational environments for Machine Situational Awareness, particularly within contested, congested and degraded scenarios.
  • Fully autonomous robust intelligence data processing to significantly reduce the reliance upon human analysts and counter huge increases in data volumes.
  • Improved synthetic training utilising machine-based instructors, matched to individual training needs.
  • Improved “Virtual Assistants” for the next generation of platform-operator interfaces.

The work is envisioned to have great impact on design and development of intelligent autonomous agents.

Fully funded PhD covering not only tuition, fees and bursary but opportunity to attend conferences and to link with industrial experts in the field.

The applicant is envisioned to further enhance and develop world class skills in AI and Machine Learning with application to hard and challenging defence problems providing a great skill set for employability after the degree in both industry but also academia as well.

Entry Requirements

Applicants must have a B.Sc. in engineering or a related area and must either have or close to having a Master’s degree (must be completed by the time of the start of the iCASE Award). A demonstrated background in aerospace, autonomy and AI/ML would be a distinct advantage. 

This PhD is open to students from the UK, EU and NATO countries, that meet certain security conditions. The student will be working in sensitive topics and must be able to pass vetting and gain security clearance.

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