Projects per year
Organisation profile
Organisation profile
Our School of Physics, Engineering and Computer Science provides businesses, industry and the public sector with talented graduates that have the skills and advanced knowledge to work effectively in the modern, high technology, world that drives economies and society. We focus on equipping students with practical and theoretical skills to solve the challenges of our ever-evolving world, and providing world leading and international excellent research that underpins innovation and enterprise.
Our school is home to some of the UK’s best teaching facilities - a planetarium widely recognised as one of the best teaching facilities in the UK, a variety of flight simulators, aerodynamic wind tunnels, specialist cyber security, artificial intelligence and robotics labs. Not only do these cutting-edge facilities enable students to develop the practical skills they need to gain their dream career, they also provide an exciting and stimulating environment for our staff to develop their own careers.
No matter what role or discipline you are drawn to within the school, you can be assured that you will be joining a passionate and dedicated department that is driven by expertise and excellence, known for its leading research and fantastic facilities. Our school is a fantastic environment to begin your career, whether you are joining us as an academic, or in a research or leadership role, we are devoted to nurturing talent and helping you succeed!
Academic subject areas:
- Aerospace engineering
- Astronomy
- Automotive engineering
- Civil engineering
- Computer science
- Cybersecurity
- Data science
- Electrical and electronic
- Engineering
- Information technology
- Mechanical engineering
- Mathematics
- Physics
- Robotics and artificial intelligence.
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Collaborations and top research areas from the last five years
Profiles
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Holistic Mapping for EV Fast Charging Integration in Distribution Networks
Khalil, S. (PI)
1/02/26 → 31/01/28
Project: Research
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Power System Vulnerability Detection and Stability Enhancement via Distributed Machine Learning
Khalil, S. (PI)
1/01/26 → 31/12/27
Project: Research
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Royal Society URF: A Multi-Scale Exploration of Supermassive Black Holes in the Multi-Messenger Era
Koudmani, S. (PI)
1/01/26 → 31/12/33
Project: Research
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Mechanics of Epoxy Nanocomposites: A Study on the Synergy of the Reinforcements
Pir, İ., Tufekci, M., Acarer Arat, S. & Tufekci, E., 9 Feb 2026, (Accepted/In press) In: ACS Omega.Research output: Contribution to journal › Article › peer-review
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A class of discrete memristive hyperchaotic maps with multi-cavity multi-structure attractors and its application in secure communication
Yang, G., Wang, C., Sun, Y. & Deng, Q., 7 Feb 2026, (Accepted/In press) In: IEEE Transactions on Industrial Informatics.Research output: Contribution to journal › Article › peer-review
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A Discrete Memristive Hopfield Neural Network With Grid Multi-structure/scroll-like Attractors
Yang, G., Wang, C., Sun, Y. & Deng, Q., 6 Feb 2026, (E-pub ahead of print) In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 11 p.Research output: Contribution to journal › Article › peer-review
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