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Whole-body loco-manipulation for robotic inspection of energy industry equipment

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GBP 25 000 - 35 000
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Whole-body loco-manipulation for robotic inspection of energy industry equipment

The University of Manchester
Grã-Bretanha
GBP 25.000 - 35.000
Descrição da oferta de emprego

This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero (RAINZ CDT), a partnership between three of the UK’s leading universities: The University of Manchester, University of Glasgow, and University of Oxford.

Robotics and Autonomous Systems (RAS) are crucial for the UK’s energy sector’s Net Zero transition. However, technological and cultural barriers limit their effectiveness. This CDT aims to address these challenges by focusing on how RAS can be used for inspecting, maintaining, and repairing infrastructure in renewables (wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), supporting decarbonization of existing assets.

We seek talented graduate scientists and engineers eager to learn and contribute to increasing RAS applications in the energy sector. Your work will foster innovation and drive meaningful change in this vital field.

RAINZ_CDT

Year 1: You will undertake MSc studies and research training at The University of Manchester. You must achieve at least 65% in your MSc assessments to progress to the PhD.

Note: You will not graduate with an MSc. If you meet the criteria, you will transition directly to the PhD.

Years 2–4: You will conduct your PhD research at your host university (Manchester, Glasgow, or Oxford), complemented by training and employability development programs.

About this Project

Year 1 MSc Course: MSc Robotics

Years 2–4 PhD Location: The University of Manchester

Research Abstract: Condition monitoring of industrial equipment, such as turbomachinery, involves complex data collection often hindered by size, complexity, and harsh conditions. This research addresses two challenges: (1) optimizing sensor movement for inspecting large, complex equipment with robots and manipulators, and (2) ensuring high-quality data collection under harsh conditions.

Eligibility

Applicants should hold a First or strong Upper Second-class honours degree (2:1 with 65% average) in Engineering, Computer Science, Physics, or Mathematics, with programming experience.

Before You Apply

It is recommended to contact the project supervisor(s) beforehand. Include your current study level, academic background, relevant experience, and motivation for applying.

How to Apply

Applications should be submitted via the RAINZ CDT website. For inquiries, email rainz@manchester.ac.uk.

When applying, specify the project name, supervisor, funding status, previous study details, and contact information for two referees.

Ensure all required documents are submitted; incomplete applications will not be considered. Supporting documents include:

  • Final transcripts and certificates
  • Interim transcripts (if applicable)
  • CV
  • Motivation statement (mandatory)
  • Referee contact details
  • English Language certificate (if applicable)

The deadline is 17:00, 11th July 2025.

EDI

Equality, Diversity, and Inclusion are central to RAINZ CDT’s values. We encourage applicants from diverse backgrounds and support flexible working arrangements. Our process is fair and unbiased, promoting equal opportunities for all.

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