Skip to main content
What types of page to search?

Popular pages: Undergraduate Postgraduate PhD Accommodation Research International students

Alternatively use our A-Z index.

Accelerating Laboratory Automation Through Learning Tool Morphology For Robotic Chemists

Funding
Funded
Study mode
Full-time
Start date
Subject area
Computer Science
How to apply
Change country or region

We’re currently showing entry requirements and other information for applicants with qualifications from United Kingdom.

Please select from our list of commonly chosen countries below or choose your own.

If your country or region isn’t listed here, please contact us with any questions about studying with us.

Overview

In this project, you will develop an intelligent robotic system that uses a co-design learning framework to autonomously design and produce specialised tools for complex chemistry lab tasks, including handling heterogeneous materials.

About this opportunity

Accelerating chemical and materials discovery is crucial for future societal and industrial impact. We urgently need to design and discover the materials required to build a more sustainable, prosperous, and healthy future. The future of chemical discovery, leveraging methods like generative AI, will depend heavily on data from autonomous robotic experiments.

 

While autonomous robotic chemists have shown promise [1-2], they still struggle with complex tasks like sample preparation, as they lack the dexterity to handle the diverse, unpredictable materials found in labs.  During this project, we will address this bottleneck by developing a novel robotic chemistry tool optimisation system for handling heterogeneous materials, building on our previous works [3-5]. In collaboration with Dr. Kevin Luck, we will develop a co-design learning framework to improve laboratory skill learning by optimising tools for robotic manipulators. Subsequently, we will automatically design, produce, and test these new tools in laboratory tasks with our industrial partners. This approach aims not only to advance chemistry lab automation but also to develop novel robotic methods for material manipulation across different domains.

This project offers a unique opportunity for you to:

  • Develop intelligent robotic systems capable of adapting to the complexities of heterogeneous materials using novel tools
  • Design a fully automated tool design pipeline that takes the learned tool specifications, prints the tool, and evaluates their performance.
  • Deploy and validate the robotics system in real-world labs at the University of Liverpool and in collaboration with our industrial partners e.g., Unilever.
  • Collaborate with external partners in our collaborative network of ongoing multidisciplinary projects.

The project will be supervised by Dr Gabriella Pizzuto (Computer Science/Chemistry) and contribute towards cutting-edge robotics research in AI-driven robotic scientists at the University of Liverpool at the Autonomous Chemistry Labs in the Digital Innovation Facility and Materials Innovation Factory, focused on their deployment in real-world applications. You will also have the opportunity to work with our internal collaborators such as Prof. Andy Cooper’s group and external partners on our ongoing multidisciplinary projects.

The studentship is aligned with an EPSRC New Investigator Award project.

Further reading

[1] A. Lunt, H. Fakhruldeen, G. Pizzuto, L. Longley, A. White, N. Rankin, R. Clowes, B. Alston, L. Gigli, G. M. Day, S. Y. Chong, and A. Cooper, Modular, Multi-Robot Integration of Laboratories : An Autonomous Workflow for Solid-State Chemistry, Chemical Science, 2024.

[2] A. I. Cooper, P. Courtney, K. Darvish, M. Eckhoff, H. Fakhruldeen, A. Gabrielli, A. Garg, S. Haddadin, K. Harada, J. Hein, M. Hubner, D. Knobbe, G. Pizzuto, F. Shkurti, R. Shrestha, K. Thurow, R. Vescovi, B. Vogel-Heuser, A. Wolf, N. Yoshikawa, Y. Zeng, Z. Zhou, H. Zwirnmann, Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges, Science Robotics, 2025.

[3] G. Pizzuto, H. Wang, H. Fakhruldeen, B. Peng, K.S. Luck and A. I. Cooper, Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping, IEEE CASE, 2024 (Best Healthcare Automation Paper Finalist).

[4] Y. Jiang, A. He, H. Fakhruldeen, G. Pizzuto, L. Longley, T. Dai, R. Clowes, N. Rankin, and A.I. Cooper, Autonomous Solid Dispensing using a Dual-Arm Robotic Manipulator For Laboratory Workflows, Digital Discovery, 2023.

[5] N. Radulov, A. Wright, T. Little, A. I. Cooper and G. Pizzuto, FLIP : Flowability-Informed Powder Weighing, arXiv pre-print, 2025.

Back to top

Who is this for?

This project is open to UK and international applicants; however, due to the nature of the funding we are only able to cover home fees only. Candidates will have, or be due to obtain, a master’s degree or equivalent related to Engineering or Computational Science, or an international equivalent. Exceptional candidates with a First Class undergraduate degree or international equivalent in an appropriate field will also be considered. The minimum English Language requirements for international candidates is IELTS 6.5 overall (with no band below 5.5) or equivalent. Find out more about English language requirements.

We want all our staff and students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We’re committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances.

Back to top

How to apply

  1. 1. Contact supervisors

    We strongly encourage applicants to get in touch with the supervisory team to get a better idea of the project before making a formal application online. Please contact:

    Dr Gabriella Pizzuto

  2. 2. Prepare your application documents

    You may need the following documents to complete your online application:

    • A research proposal (this should cover the research you’d like to undertake)
    • University transcripts and degree certificates to date
    • Passport details (international applicants only)
    • English language certificates (international applicants only)
    • A personal statement
    • A curriculum vitae (CV)
    • Contact details for two proposed supervisors
    • Names and contact details of two referees.

  3. 3. Apply

    Finally, register and apply online. You'll receive an email acknowledgment once you've submitted your application. We'll be in touch with further details about what happens next.

    Application deadline is 31st January 2026; however, we will close the application once a suitable candidate is found hence early application is advised. We will interview on a rolling basis and fill the position on a first come, first served principle.

Back to top

Funding your PhD

This studentship will cover full tuition fees and pay a maintenance grant for 4 years, starting at the UKRI minimum of £20,780 per annum for academic year 2025-2026. The studentship also comes with a Research Training Support Grant to fund consumables, conference attendance, etc.

This studentship are available to any prospective student wishing to apply including both home and international students; however, due to the nature of the funding we are only able to cover home fees. If you have a disability you may be entitled to a Disabled Students’ Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.

Back to top

Contact us

Have a question about this research opportunity or studying a PhD with us? Please get in touch with us, using the contact details below, and we’ll be happy to assist you.

Dr Gabriella Pizzuto
Back to top