Job title
Fully Funded PhD Research Studentship
Job reference
REQ001431
Date posted
23/12/2024
Application closing date
20/01/2025
Location
Dundee
Salary
A tax-free stipend of £18,622
Contractual hours
35
Basis
Full time
Job category/type
Design, Informatics and Business
Attachments
Blank
Job description
Fully Funded PhD Research Studentship
Project Title: Privacy-Preserving Machine Learning for Next-Generation IoT (NG-IoT) Security
PhD Studentship: R-LINCS2 funded. The Studentship is available for June/ October 2025 start.
This PhD studentship comprises a tax-free stipend of £18,622 (increasing in line with UKRI per annum) per year over 3.5 years, tuition fees paid, and a generous study package (e.g., limited research consumables, travel budget, and training when appropriate).
The studentship is supported by both the Abertay Graduate School and the Faculty of Design, Informatics and Business. The pan-University Graduate School offers an integrated training programme to the postgraduate community within a single centre, serving to inculcate interdisciplinary work in our next generation of researchers. Training sessions include research design, data analysis, academic paper and grant writing, and thesis and viva preparation.
The Faculty of Design, Informatics and Business has over one hundred academic staff with expertise in cybersecurity, computer games, business and law. Please see the “Abertay University" section below for more details.
Project Description: The Next-Generation Internet of Things (NG-IoT) represents a cutting-edge advancement in technology, enhancing everyday life through intelligent environments and more efficient use of network resources. The rapid growth of IoT has caused an explosion in data generation, shifting analytics and Machine Learning (ML) processes to the edge. However, combining IoT and ML at the edge (IoT-ML fabrics) brings challenges, particularly regarding data privacy. IoT devices often produce highly sensitive data tied to personal spaces and activities, making them vulnerable to theft or manipulation. Without adequate privacy safeguards, ML models face security risks such as data poisoning, malicious actors, free riding, and distributed denial-of-service (DDoS) attacks. Blockchain technology offers a solution by enabling secure, decentralized peer-to-peer interactions among untrusted devices, establishing a robust NG-IoT framework. This initiative aims to integrate distributed ML with blockchain to ensure secure and efficient learning in NG-IoT while addressing prevailing cybersecurity challenges.
Key Deliverables:
Prototype an IoT-ML fabric: Determine and create a prototype IoT-ML fabric with IoT and ML integration at the edge.
Privacy-Preserving ML Approach: Develop and demonstrate a privacy- preserving ML approach using blockchain that ensures the security of data in NG-IoT, addressing data privacy issues inherent in current IoT-ML frameworks.
Cybersecurity Evaluation: Assess the developed privacy-preserving ML approach in real-time security context and its efficacy in enhancing network security.
It is anticipated that the output of this research will be of widespread and significant benefit to the industry, leading to improved cybersecurity defense and wide-ranging implications. A major project requirement is to embed expertise by capturing good industrial and academic practices and disseminating that knowledge widely. The theoretical underpinning and novelty of the research will contribute to the academic fields of data science, computing, and cybersecurity. Research findings will be disseminated to both academic and public audiences, building both theoretical advances and real- world impact.
Supervisory Team: The candidate will be supervised within the Department of Cybersecurity and Computing by an inter-disciplinary team led by Dr Shailendra Rathore. Queries on this project should be directed to Dr. Shailendra Rathore ([email protected]).
Entry Requirements: Candidates must have, or expect to obtain, a first class or upper second-class Honors degree in computing or engineering (or equivalent). We are looking for an independent, enthusiastic, and driven candidate with a basic understanding of networking, ML, and/or blockchain development. Applicants should have experience in programming (e.g., designing and running ML models).
Candidates must work well with others and represent the university when working with key stakeholders (e.g., the industry).
For applicants who are non-native speakers of English, the University requires IELTS of 6.5 (with no band less than 6.0) or an equivalent qualification accepted by the Home Office.
Applications and closing date : 20 .01.2025
Applicants should submit through the Abertay University jobs page https: // www. abertay.ac.uk/about/working-at-abertay/jobs/, submitting a personal statement of application detailing why you are interested in undertaking this project, and a CV.
If you are selected for an interview, you will be required to complete an online Research Student Application Form which includes the submission of a research proposal. Guidance on how to write the proposal can be found here: https: // www. abertay.ac.uk/study-apply/how-to-apply/how-to-apply/, Applicants are strongly encouraged to contact Dr Shailendra Rathore ([email protected]) for advice on developing a proposal prior to submitting it.
Abertay University has a particular focus on industry-facing cybersecurity research that addresses critical challenges in securing digital systems and safeguarding data in an increasingly interconnected world. The Abertay CyberQuarter is an £18M R&D Centre fostering collaboration between academia and industry to solve global cybersecurity challenges, advance innovation, and expand career opportunities. Through the cyberQuarter, candidate will have the opportunity to regularly liaise with industry and academia partners to formulate research and curriculum relevant to security topics. Our research focuses on areas including secure software development, ethical hacking, advanced threat detection, and emerging technologies such as blockchain, IoT and artificial intelligence. According to the results of the Research Excellence Framework 2021, Abertay recorded 60% of its research judged as 'internationally excellent' or 'world-leading', a 23% increase since the last REF2014 – the biggest climb of any Scottish university. Abertay University is the UK Cyber University of the Year at the National Cyber Awards 2024 andis recognised by the UK National Cyber Security Centre (NCSC) as an Academic Centre of Excellence in Cyber Security Education, with a gold award. We hold an Athena SWAN Institutional Bronze award and were the first Scottish university to achieve the Race Equality Charter Mark.
Entry requirements
Essential requirements:
Desirable requirements (but not essential)
First class or upper second-class honours degree (or its equivalent) in computing, engineering, or a closely aligned discipline.
Master of Science level qualification in a relevant discipline.
Experience in computer networking and ML and /or Programming (e.g., designing and running ML model).
Working experience of blockchain development, edge computing, and/or IoT security.
Coding experience (e.g., C, C++, Java, Python)
Proficient in programming languages such as C, C++, Java, and Python, with a focus on IoT-ML integration and blockchain development.
Good scientific and academic writing.
Involvement in the preparation of articles for publication in scientific journals, showcasing a proactive approach to academic dissemination and collaboration.
Good numerical, statistical, and mathematical skills.
Knowledge of advanced statistical methods, enhancing the ability to analyze and interpret complex data associated with NG-IoT and ML.
Good interpersonal and communication skills.
Applicants who are non-native speakers of English, the University requires IELTS of 6.5 (with no band less than 6.0) or an equivalent qualification accepted by the Home Office.