Computational nanorobotics with machine learning

About the Project

Supervisory Team: Ondrej Hovorka and Ivo Peters

The project develops intelligent nanorobots for autonomous control and adaptive behaviour in liquid nanoscale environments, exploring algorithms for simulation, control, and prediction with applications in drug delivery, diagnostics, and nano-manipulation.

The Department of Aeronautics and Astronautics at the University of Southampton is inviting applications for a PhD position in computational nanorobotics with a focus on integrating machine learning techniques.

This project aims to develop intelligent nanorobotic systems capable of autonomous decision-making, optimized control, and adaptive responses in complex liquid nanoscale environments.

You will explore machine learning algorithms for simulation, control, and predictive modelling of nanorobots, with potential applications in targeted drug delivery, molecular diagnostics, and precision nano-manipulation.

What we offer:

• access to state-of-the-art research facilities and a collaborative, interdisciplinary team
• mentorship from leading experts in nanotechnology, robotics, and machine learning
• opportunities for publishing in top journals and presenting at international conferences

Entry requirements

You must have a UK 2:1 honours degree, or its international equivalent in one of the following or a related field:

• computer science
• engineering
• physics

You must have:

• strong background in machine learning, computational modelling, and algorithm design
• experience with nanotechnology, robotics, or related areas (is preferred)
• proficiency in programming languages (e.g., Python, C++)
• familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)
• excellent analytical and problem-solving skills

Fees and funding

We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.

Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.

Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.

How to apply

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)

Contact us

Faculty of Engineering and Physical Sciences

If you have a general question, feps-pgr-apply@soton.ac.uk.

Project leader

If you wish to discuss any details of the project informally, please contact Dr Ondrej Hovorka (o.hovorka@soton.ac.uk).