PhD Studentship: Robotic Platforms for AI Empowered Nanomaterial Synthesis

   Department of Chemical Engineering

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  Dr Max Besenhard  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project


The Department of Chemical Engineering at UCL ( is one of the top research and teaching departments in the UK, with world-class standing. The department offers several undergraduate and postgraduate programmes and has an extensive research portfolio across a wealth of areas, including advanced functional materials and autonomous systems. The department hosts 35 academics undertaking collaborative, ground-breaking research, focused on solving many of the grand challenges for society.

The advertised research will be conducted in UCL’s brand new and cutting-edge Manufacturing Futures Laboratory (MFL) at the beautiful Queen Elizabeth Olympic Park. The MFL is a truly interdisciplinary facility, bringing together core expertise from several departments, enabling the development of new strategic research, focused on knowledge-based manufacturing to deliver the advanced functional materials and sustainable products and processes of the future.

The post is fully funded for 3.5 years starting September 2024.


Robotics and automation are rapidly changing research and development in all areas of science and engineering. Empowered by Artificial Intelligence & Machine Learning autonomous robotic systems facilitate new ways for material discovery, providing a much needed strategy to develop materials that solve the grand challenges of society. This project focusses specifically on nanomaterials for biomedicine (especially magnetically induced cancer treatment and MRI contrast agents) and energy materials (e.g. solar cells and battery materials).

Synthesising nanomaterial with properties (e.g. size, composition, surface chemistry) well-tuned for the targeted application is incredibly complex as a high number of synthesis variables affects the final product. The experimental demands scale exponentially with the number of variables like reactants, reaction conditions and concentration and temperature profiles. Hence, scientists must restrict their search spaces dramatically despite seeking highly advanced nanomaterials. This usually leads to insufficient results or unrealistic experimental campaigns which severely limits innovation in nanomaterial science. This project aims to benefit from the opportunities robotic systems (and especially liquid handling robots) provide to automate nanomaterial synthesis.

Reactors commonly used to synthesise nanomaterials in the lab are rather simple but their integration into state of the art liquid handling robots has not been fully utilised. One reason for this is the size constraints all commercially available liquid handling robots impose, as they were developed and standardised to handle small liquid volumes. In addition, material characterization still requires manual sample transfer and sample preparation. Within this PhD the student will design small and compact chemical reactors that can be integrated within available robotics platforms, and develop workflows to facilitate the execution of synthetic procedures in these reactors autonomously, i.e., without experimental effort for the human operator. Furthermore, specialised analytic equipment analysing nanomaterials in real-time will be integrated within these robotic platforms and made part of the workflow to “close the loop”. This allows for fully autonomous nanomaterial development by coupling this robotic platform for nanomaterial synthesis and analysis with Artificial Intelligent algorithms. Such smart robotic platforms will make it possible to develop novel synthetic procedures yielding advanced functional nanomaterials for biomedicine and energy materials.


The successful candidate will have completed or be close to completing a first-class degree at the MEng or MSc level in Chemical Engineering, Biochemical Engineering, Electrical Engineering, Computer Science, Physics, Chemistry, Material Science or any related science or engineering discipline. The successful candidate will be a motivated student, with an interest in the areas of material science (e.g. nanomaterial synthesis and characterisation), energy and biomedicine, automation and robotics, and artificial intelligence/machine learning.

The ability to work independently while being a productive member in a collaborative team, within the context of a dynamic research field and a demanding environment, is a must. Demonstrable prior experience in the field of material science or automation are desirable, but not necessary requirements. The post-holder will have the opportunity to present results at international conferences and publish in peer-reviewed journals of high international standing.


First-class degree at the MEng or MSc level is required.

Funds are only available to cover UK-equivalent fees. Overseas applicants may apply but if successful would have to find funding to cover the difference between the UK and overseas fees rates.

Applications should be submitted through:

Please nominate Dr. Maximilian Besenhard as supervisor and include a statement of interest.

For informal enquiries please contact Dr. Maximilian Besenhard at [Email Address Removed].

For further information on the MPhil/PhD course as well as the recruitment and selection process, please click on the link below:

Biological Sciences (4) Chemistry (6) Computer Science (8) Engineering (12) Materials Science (24) Physics (29)

Funding Notes

Stipend: c. £21,000 (in line with the UCL rate) + UK fees
Duration of Studentship: 3 years fees and 3.5 years stipend
Start date: September 2024