Funding

Self-funded

Project code

COMP6261025

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 Uchenna Ogenyi.

 

The work on this project will:

  • Create algorithms enabling real-time recognition and adaptation to dynamic changes in the environment relevant to robotic arm operations.
  • Formulate methodologies for task-specific adaptation, ensuring that robotic arms can dynamically adjust their movements based on the requirements of different tasks.
  • Incorporate ethical considerations into robotic arm operations, addressing issues such as human-robot collaboration, safety, and privacy.
  • Validate transfer learning techniques in practical scenarios representative of diverse robotic arm applications, ensuring real-world applicability.

Context

The project aims to represent a novel initiative to enhance the adaptability and efficiency of a robotic arm in a complex and evolving operational environment. The principal objective is to introduce scalable transfer learning methodologies, enabling a robotic arm to seamlessly apply acquired knowledge across diverse environments.

Furthermore, the project seeks to establish methodologies for task-specific adaptation, allowing a robotic arm to dynamically adjust its movements based on the requirements of different tasks. Metrics will be defined to quantify the transferability of learned knowledge across distinct robotic arm environments. Real-time adaptation mechanisms will be implemented to facilitate prompt adjustments to dynamic environmental changes.

The integration of knowledge from multiple domains within robotic arm applications will be explored, fostering versatility. Practical scenario validation will ensure the applicability of transfer learning techniques in diverse robotic arm applications. Ethical considerations, such as human-robot collaboration, safety, and others, will be incorporated into the fabric of robotic arm operations. The project concludes with rigorous documentation of methodologies, algorithms, and findings, fostering knowledge dissemination within the robotics community and promoting broader understanding and application. Overall, this project aspires to revolutionize robotic systems, establishing new benchmarks for safe, efficient, and responsible human-robot interactions in dynamic and heterogeneous environments.

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 (conditions apply).

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

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Applicants should possess an understanding of the core principles in robotics, computer vision, and machine learning techniques. A good knowledge of  Python/C++ programming, good analytical skills, and a foundation in computer science or related fields are essential requirements. The ideal candidate must demonstrate the ability to think critically and independently, including the formulation of research problems. Additionally, effective oral and written communication skills, along with proficient time management, are highly valued.

 

How to apply

We’d encourage you to contact Dr Uchenna Ogenyi (uchenna.ogenyi@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: COMP6261025