Funding

Self-funded

Project code

CMP10031025

Department

School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Fahad Ahmad.

The work on this project will:

  • Use a specific QML algorithm for pattern recognition and anomaly detection tailored to the IoMT environment.
  • Construct a working prototype that integrates the QML algorithms with IoMT. This system will be tested on simulated IoMT networks to evaluate its effectiveness in real-time threat detection and mitigation.
  • Perform rigorous testing of the prototype under different scenarios to validate security effectiveness, speed, and accuracy. Refine the algorithms based on the testing outcomes.

The increasing use of Internet of Medical Things (IoMT) devices has exposed medical networks to heightened cybersecurity risks. Conventional security systems are often inadequate in handling the complex and growing volume of these threats effectively. Quantum Machine Learning (QML) presents a viable solution by utilizing the advanced capabilities of quantum computing to process information with greater speed, efficiency, and security than traditional methods.

 

The primary goal of this project is to develop a prototype using QML, with a focus on Generative Models (GM), to bolster the security of IoMT systems. This initiative aims to establish a system capable of accurately predicting and immediately neutralizing potential security threats, thereby safeguarding the integrity and confidentiality of medical data.

 

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

 

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a master’s degree in computer science or a related area. In exceptional cases, we may consider equivalent professional experience and/or Qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

You must have skills in machine learning, internet of tings, and quantum computing.

Desirable skills in networks, and cyber security.

 

 

 

 

How to apply

We’d encourage you to contact Dr Fahad Ahmad (fahad.ahmad@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: CMP10031025