Artificial Intelligence, Security, IoT: Fully Funded PhD Studentship in Adversarial Learning in[...]

Organisation/Company: Swansea University

Department: Central Research

Field: Computer science » Other

Researcher Profile: First Stage Researcher (R1)

Positions: PhD Positions

Country: United Kingdom

Application Deadline: 13 Jan 2025 - 23:59 (Europe/London)

Type of Contract: Temporary

Job Status: Full-time

Offer Starting Date: 1 Oct 2025

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Funding provider: EPSRC DTP

Subject areas: Artificial Intelligence, Security, IoT

Aligned programme of study: PhD in Computer Science

Mode of study: Full-time

Project description:
Edge devices, integral to the Internet of Things (IoT) and modern smart applications, have increasingly relied on artificial intelligence (AI) for efficient operation and decision-making. However, these AI-based systems are vulnerable to adversarial attacks, which can compromise their functionality and security. This project aims to investigate the vulnerability of machine learning models deployed on edge devices and develop robust adversarial learning techniques to defend against such attacks. The focus will be on identifying potential weaknesses in current edge computing frameworks and leveraging adversarial learning, edge computing, and game theory to create novel methods to enhance their resilience. This includes developing algorithms capable of detecting and mitigating adversarial attacks, ensuring that edge devices can maintain secure and reliable operations even under hostile conditions. Our research will cover various applications of edge devices, including real-time data processing, autonomous decision-making, and network intrusion detection. By addressing these areas, we aim to create a framework that not only secures individual edge devices but also enhances the overall security of interconnected IoT systems. The outcomes of this project will provide critical insights and methodologies for deploying secure, AI-driven edge solutions, thereby fostering safer and more reliable IoT ecosystems.

Minimum Requirements

Candidates must hold a UK Bachelor degree with a minimum of Upper Second Class honours in Computer Science, Mathematics, or a closely related discipline, or an overseas Bachelor degree deemed equivalent to a UK Bachelor (by UK ECCTIS) and achieved a grade equivalent to UK Upper Second Class honours in Computer Science, Mathematics, or a closely related discipline.

Or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).

IELTS 6.5 Overall (with no individual component below 6.0) or Swansea University recognised equivalent.

ATAS clearance: IS NOT required to be held as part of the scholarship application process. Successful award winners (as appropriate) are provided with details as to how to apply for ATAS clearance in tandem with a scholarship course offer.

Additional Information

This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £19,237 for 2024/25).

Additional attending conferences expenses of up to £1,000 per year will also be available.

EPSRC DTP studentships are available to home and international students. Up to 30% of our cohort can comprise international students; once the limit has been reached, we are unable to make offers to international students.