PhD Studentship in Robotics and AI Robust Perception for Robots in Complex Processes Open World

From safer surgery to sustainable factories and net-zero supply chains, we increasingly rely on robots to do work that is difficult, repectitive, or chronically understaffed. To be truly useful, these robots must perceive, plan, and act in open-world conditions: never-seen objects, shifting lighting, clutter, domain shift, and multi-task requirements. These factors challenge current robotic systems. This PhD will design methods that enable robots to achieve more robust, accurate perception and perception-driven planning for complex processes.

You will investigate solutions like multi-sensing fusion (e.g., RGB-D, thermal, LiDAR, tactile), universal perception frameworks (e.g., Vision-Language-Action (VLA) models, Transfer Learning, self-supervised learning) that generalise across tasks and scenarios in engineering applications, and their tight integration with planning and control (e.g., task-and-motion planning, differentiable planning, or Reinforcement Learning (RL) with safety constraints). There will be opportunities to validate on real systems across interdisciplinary domains, including medical robots, manufacturing/re-manufacturing automation, and inspection robots.

Candidate Requirements:

Essential
• First-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field.
• Knowledge of machine learning/deep learning and experience in two or more of: computer vision, sensors/sensor fusion, robotics fundamentals.
• Proficient in programming languages such as Python and C++; experience with frameworks such as PyTorch, TensorFlow, OpenCV.
• Strong problem-solving, communication, and a passion for building real systems.

Desirable
• Experience with ROS/ROS2 and real robotic platforms.
• Knowledge of electronic sensors and embedded systems development.
• Experience with 3D modelling /CAD.
• Publications, competition results, or an active GitHub/portfolio.

Research Environment
The University of Birmingham is one of the top-ranking universities in the UK and globally. The successful candidate will join a collaborative lab within the Birmingham Robotics Institute, School of Engineering, with access to robotic arms, mobile platforms, industrial sensors/cameras, GPU workstations, and cloud platforms. Training covers research methods, scientific writing, open-source best practices, and impact/engagement. You’ll be encouraged to publish at top venues (e.g., ICRA, IROS, CoRL, RSS, CVPR, IEEE Transactions) and collaborate with industry/health partners where appropriate.

Preferable start date: First half of 2026

More details of entry & language requirements can be found at:

https://www.birmingham.ac.uk/study/postgraduate/subjects/mechanical-engineering-courses/mechanical-engineering-phd

Funding notes:

• Home (UK) applicants: Full tuition + stipend at the UKRI rate for 42 months.
• International applicants: The studentship covers the Home fee and stipend. Outstanding candidates are welcome if they can cover the fee difference via self-funding or external sources.

If you meet the requirements and are interested, please send your academic CV and personal statement to Dr Jiaqi Ye – j.ye@bham.ac.uk

It is advised to refer to the following when preparing your CV and personal statement.
• How to Write a PhD CV: https://www.findaphd.com/guides/phd-cv
• A Guide to PhD Personal Statements: https://www.findaphd.com/guides/phd-personal-statement

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