SPADS also includes a suite of cohort development activities including summer schools, participation in industry challenges and a hackathon. These elements are all explained in more detail below.

1. The taught component

SPADS students take 180 credits’ (Cr) worth of courses, of which: a) 60Cr form a compulsory "core" of courses that include 20Cr of courses co-created with industry to cover bespoke CPD needs for a successful career in the defence & security sector, b) 80Cr are chosen as electives, and c) 20Cr are obtained in the form of a placement.

1.1 Core courses 

The core courses are designed to provide a solid, common competency in key, highly transferrable skills and link together all students in the programme via a common language and basis for being professional engineers. These include:

Year 1

• Engineering research methods: Knowing how to access and assess the quality of information, as well as understanding the context of research and how it interacts with business, ethics and security are key skills for any defence engineer. This course covers all these aspects and is industry-led.
• Introduction to sensing and measurement: This course consists of 5x modules, each addressing an individual application topic, including “applications of sensors in industry”, “sensing with memristors”, “metrology and measurement”, “machine learning for sensing”, and “RF sensing”, covering a range of technologies from the well-established to the midterm future. The modules will be designed and delivered with partner institutions.
• Software testing: Designing for high quality is no small endeavour. Especially when safety-critical systems are involved, the ability to test software methodically and ensure high scenario coverage and compliance with regulations is a key skill. This course seeks to teach the methods and instil the discipline and rigour required to write top-quality code, from new AI algorithms to testing microchips for use in aerospace hardware.

Year 2 

• Case Studies in AI Ethics: Artificial intelligence (AI) is being deployed in real-world settings more than before. Especially, fully automated AI systems started to make critical decisions such as who should be employed or who is a criminal. In this course, the students will increase their understanding of data ethics. The course gives an overview of the ethical issues (e.g. bias, fairness, privacy) and brings together different case studies from various contexts. The students will analyse case studies to identify and mitigate potential risks considering legal, social, ethical or professional issues.

• A two block-taught bespoke training delivered from both academia and our industry partners following the summer school model.  These defence specific modules give students a unique training experience through exposing them to innovative courses, alongside additional electives (30Cr). While these courses are still under development, our co-created courses intend to cover (i) “Sensors and Sensing for Defence” and (ii) “Complex Defence & Security Systems”. 

1.2 Elective courses

The elective courses are taken from a list of 100+ courses available at the participating universities. Most electives belong to one of the following “specialist themes” that you may choose to develop your career in:

• Systems engineering and interfaces – learning how to create large and complex systems: Includes 30+ systems engineering courses such as “biologically inspired computation”, “robot systems science”, and “systems thinking and practice”, but also includes systems engineering related topics such as programming courses spanning all levels (python to threaded, secure, and industrial programming). The interfaces element covers courses from database design and numerical computational methods for high-performance computing.
• Communication systems and RF engineering – building intelligent, adaptive, and multifunctional communications systems: A set of 10+ courses including “Digital Communications”, “Coding Techniques”, “Wireless Communications”, “Array Processing & MIMO systems”, “Embedded Mobile and Wireless Systems”, “RF Engineering”, “RF & Microwave Circuits and Systems”, and “Information Theory”. Electives from this theme provide a strong foundation for research in information communication, extraction, and delivery of signals in complex and congested electromagnetic environments.
• Signal processing, machine learning and algorithms – inventing the AI algorithms of tomorrow: 25+ engineering-oriented courses from “digital signals analysis”, “ML in signal processing”, and “image processing”, through to computer science-oriented courses in the “algorithmic foundations of data science”, “applied ML”, “probabilistic modelling and reasoning”, and “RL”. Mathematics courses in this theme include “Bayesian Data Analysis & Theory”, “Fundamentals of Optimisation”, “Numerical probability and Monte Carlo simulation”.
• Sensors and sensing – building the eyes, ears, and skins of military hardware: From the attire of the future soldier to drones, sensors are going to be key components; (radar) RF, electro-optical and infra-red video and lidar sensors, acoustic, vibration, neuro-inspired sensing, quantum, gyroscopes, moisture, pressure, and hyper-spectral imaging. This area is covered by courses such as “Applications of Sensor & Imaging Systems”, “Sensors and Instrumentation”, “Adaptive Signal Processing”, Computer Science and Mathematics (“Advanced Vision”, “Optimisation” & “Deep Learning for Imaging and Vision”), further supported by courses linking the fundamentals of sensors with AI (“ML and Pattern Recognition”, “Neural Information Processing”).
• AI hardware design – designing the next generation of electronics: The profile of computation in AI workloads is so different from conventional Von Neumann-based hardware that there has been an explosive growth in AI hardware accelerator innovations. This involves significant electronics design from tailor-made integrated circuits, through reconfigurable system development (e.g. FPGAs) all the way to embedded system design. This theme offers 10+ courses -including substantial laboratory practice- covering all levels of design, such as “Analogue IC” and “Circuit design”, “Analogue VLSI”, “Embedded Mobile and Wireless Systems”, and “Digital Systems laboratories”. The objective of this theme is to train engineers capable of building large-scale, production-quality AI hardware systems that can deliver the computational scale and efficiency required by defence applications and meet regulatory requirements.

Remember: interdisciplinary research may lead you to multiple themes and if in doubt, your future PhD supervisor and programme representative can advise on your choice of electives.

A set of co-created courses are delivered outside normal term times in the form of “block training” and have the feel of a regular, professional training course as you are likely to be expected to join during your career as an engineer.

The placement will occur at a partner organisation. This is likely to be industry (incumbent or start-up), but it may also be a government agency or even academic institutions, depending on your career aspirations and trajectory. Its objective is to provide you with on-the-job training and connect you with potential future employers and/or collaborators.

2. The research project

In your research project you will tackle a challenge by producing new knowledge, theoretical, practical or mixed, and then document it by publishing in academic journals, your final project thesis, but also a series of other documents that may be required by your industrial sponsor or other stakeholders. At the end of your PhD you will be examined by a set of at least two examiners who are experts in your chosen field via a standard “viva voce” examination where you will have the opportunity to showcase your work and discuss its technical merits. Each PhD is a highly personalise and highly personal experience. Our vast array of potential supervisors, industrial partners and topics offer plenty of choice. A SPADS PhD is very similar to a regular PhD, only within SPADS you will be part of a much more tightly-knit cohort and have access to a number of extra activities provided for SPADS (see section on “cohort development activities”).

3. Cohort development activities

Belonging to a doctoral training programme means that your study experience moves beyond a simple combination of courses, research and placements. SPADS offers a host of additional “cohort development activities” that seek to develop your skills, network and awareness of engineering in a more “natural” environment as you will experience throughout your future career.

Summer School Lecture at the University of Edinburgh

These include:

• A summer school: A training and networking event with lectures on state-of-art topics taught by academics and industry partners.
• Specialised theme meetings: Mini workshops where narrower topics can be discussed in more depth with industrial partners; includes grand challenge sessions where industry shares their open problems.
• An annual postgraduate showcase event: A tecnology fest with opportunities to present to up to 200 attendants from industry and academia and pitch your projects and ideas.
• Presentation and public engagements skills workshops: Bespoke training for effective communication with specialists and non-specialists in science and engineering.
• An innovation and commercialisation sandpit: An opportunity to gauge the commercial viability of your ideas and learn how to build business cases, run start-up activities and raise seed funding.
• Research progress meetings: Mini-events for presenting your ideas to the other SPADS students and learn about what they are doing.
• Annual site visits to partner institutions: Opportunities to connect with industrial partners and build an understanding of their world views.
• A cohort-building event at the Firbush outdoors centre: A fun activity to destress!
• A host of smaller team-building activities: Keep up with special SPADS events as they become available