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Synthesis and Optimisation of Stimuli Responsive Metal-Organic Frameworks in Flow

This PhD studentship focuses on developing microwave flow reactor platforms for the discovery, optimisation, and scale-up of stimuli-responsive metal-organic frameworks (MOFs) with new structures and particle characteristics. Metal-organic frameworks are porous coordination polymers with great potential for applications in energy, environmental sustainability, and healthcare. The project will investigate MOF self-assembly processes and structure-property relationships using advanced characterisation techniques including X-ray and electron diffraction, electron microscopy, IR and UV-vis spectroscopies, and gas sorption. The research will be conducted in the School of Chemistry and Institute of Process Research and Development at the University of Leeds, under the supervision of Dr. Andrea Laybourn and Dr. Chris Pask. The successful candidate will join a group of over 65 scientists and engineers with world-leading expertise in closed-loop manufacturing processes, machine-learning and online analytics, supported by state-of-the-art equipment in the Bragg Centre for Materials Research. This project combines flow and materials chemistry, characterisation, and reaction optimisation, offering training in synthetic coordination chemistry, advanced characterisation techniques, machine learning and operation of flow chemistry platforms.

Sustainable High-Throughput Synthesis for Next-Generation Pharmaceutical Manufacturing

A highly competitive PhD studentship focusing on improving the sustainability of pharmaceutical production. The project involves developing and applying batch high-throughput experimentation (HTE) methods and synthetic chemistry workflows to support the transition from batch to continuous flow processes. This PhD project will work alongside a £10M+ project funded by Innovate UK and will involve collaboration with industry partners including AstraZeneca, Labman and Britest. The research will focus on designing and executing high-throughput synthetic experiments to generate datasets for machine learning-driven optimisation, developing robust synthetic routes for pharmaceutically relevant compounds, collaborating with a postdoctoral researcher to integrate HTE data into autonomous flow reactor platforms, and embedding sustainability metrics into synthetic route selection and optimisation. The studentship provides full academic fees together with a tax-free maintenance grant at the standard UKRI rate of £20,780 per year for 3.5 years, with access to state-of-the-art facilities in the Institute of Process Research and Development and opportunities to collaborate with leading industrial partners.