This fully funded PhD opportunity at the University of Liverpool focuses on the automated virtual and physical screening of organic molecules for optoelectronic device applications, including displays, sensing, catalysis, and energy. The project leverages a combination of high-throughput computational chemistry and automated experimental characterization to identify and optimize molecular materials with desirable photophysical properties such as fluorescence lifetimes, singlet-fission rates, and up-conversion efficiency. While virtual screening of conjugated molecules is well established, predicting key photophysical properties remains a challenge due to limited and inhomogeneous experimental data. This research aims to expand virtual screening capabilities to hundreds of thousands of molecules and develop automated optical time-resolved characterization methods to generate reliable datasets, enabling fine-tuning of computational models. Supervised by Professor Alessandro Troisi (Theoretical Chemistry & Spectroscopy) and Dr. John Ward (Organic Chemistry & Automation), the project benefits from expertise in high-throughput screening, prediction of photophysical properties, and automation in chemical characterization. The Materials Innovation Factory (MIF) provides state-of-the-art facilities for both computational and experimental work, and the project is part of the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry, which offers interdisciplinary training in robotics, digital methods, and materials science. The CDT program is designed in collaboration with 35 industrial partners to produce versatile researchers capable of cross-domain communication and innovation. The studentship covers full home tuition fees and a maintenance grant for four years, with additional support for research consumables and conference attendance. Outstanding international candidates may be eligible for scholarships to cover the fee difference. The University of Liverpool is committed to diversity and inclusion, offering reasonable project adaptations and support for students with disabilities or caring responsibilities. Applicants should have a strong academic background in Chemistry, Chemical Engineering, Materials Science, Physics, or related fields, and an interest in computational chemistry, spectroscopy, or automation. The application deadline is March 31, 2026, but early application is encouraged as interviews are conducted on a rolling basis. For informal enquiries, contact Professor Troisi at [email protected]. Please review the CDT guide for application instructions, and ensure you include the project title and reference number CCPR166 when applying online. Relevant references and further details can be found in the project listing and associated publications.

This PhD project at the University of Liverpool focuses on the automated virtual and physical screening of molecules for application in optoelectronic devices. The research addresses the challenge of identifying organic molecular materials with optimal photophysical properties—such as lifetimes, fluorescence yields, singlet-fission rates, up-conversion, and quenching—that are essential for advanced optoelectronic applications but currently not predictable by high-throughput computational methods. Experimental data for these properties are limited and often inhomogeneous, making reliable prediction and screening a significant scientific challenge. The project has two interdependent objectives: (1) expanding the capabilities of virtual screening for photophysical properties to datasets of hundreds of thousands of entries, and (2) developing automated optical time-resolved characterization methods to construct reliable and homogeneous experimental datasets. Achieving these goals will require the development of automated interpretation techniques for optical spectra (including absorption, excitation, fluorescence, and fluorescence lifetime), which are currently performed manually for only a few systems at a time. Supervised by Professor Alessandro Troisi (Theoretical Chemistry & Spectroscopy) and Dr. John Ward (Organic Chemistry & Automation), the doctoral student will combine computational chemistry and automated characterization methods to identify organic molecules for novel applications in electronic devices, including displays, sensing, catalysis, and energy. The supervisory team brings expertise in high-throughput screening, prediction of photophysical properties, and automation in chemical characterization, leveraging state-of-the-art facilities at the Materials Innovation Factory (MIF). This position is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry (DAMC CDT), providing comprehensive training in robotics, digital methods, chemical and physical thinking, and materials design. The program is developed in collaboration with 35 industrial partners, ensuring that graduates are flexible, employable, and able to communicate across scientific domains. The University of Liverpool is committed to diversity and inclusion, supporting reasonable project adaptations for students with disabilities, caring responsibilities, or other personal circumstances. Funding is available through the EPSRC DAMC CDT Studentship, which covers full home tuition fees and a maintenance grant for four years (2025-26 rates: £5,006 pa tuition fees, £20,780 pa maintenance grant; 2026-27 rates to be confirmed). A Research Training Support Grant is also provided for consumables and conference attendance. While EPSRC funding does not cover international fees, a limited number of scholarships are available to support outstanding international students. Disabled Students’ Allowance may be available for eligible candidates. Applicants should have a strong academic background in Chemistry, Physics, Materials Science, Chemical Engineering, or a related discipline, with experience or interest in computational chemistry, spectroscopy, automation, or optoelectronics. The project is expected to start in October 2026, and candidates are encouraged to apply early before the deadline of January 15, 2026. Informal enquiries can be directed to Professor Troisi at [email protected]. Please review the CDT guide on 'How to Apply' and ensure you include the project title and reference number CCPR166 in your application. For further details and to apply, visit the project page: FindAPhD Project Link .