Postgraduate Course: Grand Challenge in Sensing, Processing and AI for Defence and Security (PGEE11278)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Grand Challenge in Sensing, Processing and AI for Defence and Security is a course that aims to promote innovation, critical thinking and idea generation. Teams of students are assigned a Grand Challenge topic by a mentor and they work together to come up with an innovative solution. |
| Course description |
SPADS Grand Challenge is a course where students learn to work in teams to solve multi-discplinary problems in the arena of Sensing, Processing and AI for Defence and Security.
The course is student-led and designed to promote teamwork, critical thinking, and innovation. Each team (typically groups 3-5) of students is assigned a staff mentor (and an industrial mentor where possible) who they see for 1 hour per week.
The course is split into three phases:
- Phase 1 is a one-day intensive course where the morning is dedicated to learning about working in teams, innovation, and generating new ideas. The afternoon is dedicated to learning about project management and project planning. Throughout the day the students will consider case studies of commercial research.
- Phase 2 is a four-week exercise in which teams of students are given a limited choice of grand challenges, defined by SPADS industrial partners relevant to the user-led CDT, which they have to research and understand. Students are required to understand the scientific questions, social and commercial aspects of their grand challenge. At the end of this phase the students present their findings and will be assessed on the content and delivery of their presentations.
- Phase 3 is a four-week exercise in which the teams take their grand challenge and develop a proposed solution. The groups will present their new idea, including a Responsible Research and Innovation (RRI) assessment, and innovation impact analysis to a Dragons Den panel including representatives from industry partners (and Dstl if possible), who will make an investment decision on the project.
There will be a stakeholder engagement workshop between Phases 2 and 3 for the students to consult.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2026/27, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Flexible |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Seminar/Tutorial Hours 8,
Dissertation/Project Supervision Hours 8,
Feedback/Feedforward Hours 4,
Formative Assessment Hours 2,
Summative Assessment Hours 5,
Other Study Hours 153,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
16 )
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| Additional Information (Learning and Teaching) |
other study hours spent on Grand Challenge
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Written Exam %: 0
Practical Exam %: 0
Coursework %: 100
|
| Feedback |
Formative feedback may be given. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Knowledge and understanding: Students will improve their understanding of Sensing, Processing and AI for Defence and Security by studying a particular problem in detail and by hearing the results of other groups' studies.
- Practice: Students will gain experience of analysing a problem from a variety of perspectives: scientific, commercial and societal impact.
- Generic skills: Students will gain experience of the critical analysis, evaluation and synthesis of ideas at the forefront of their subject area.
- Communication: Students will learn to structure and deliver scientific and generic presentations at a professional level.
- Autonomy: Students will learn to work effectively in teams and understand the various roles that people can play in teams.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | sensing,processing,AI,defence,security |
Contacts
| Course organiser | Prof James Hopgood
Tel: (0131 6)50 5571
Email: James.Hopgood@ed.ac.uk |
Course secretary | Mrs Jacqueline Narendran
Tel:
Email: jackie.narendran@ed.ac.uk |
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