Machine - learning - molecular of

Application deadline: 15 November 2025 Stipend: approx. £21,870 per annum + fees Duration: 3 years Start date: Between January and June 2026 Vacancy Information The Department of Chemical Engineering at University College London (UCL) invites applications for a PhD studentship in molecular simulation and artificial intelligence, funded by the Marie Skłodowska-Curie Actions Doctoral Network PRIME-LEAP. The successful candidate will develop and apply machine-learning-enhanced simulation methods to investigate elementary reactivity in plasma environments. The award covers tuition fees and a stipend for three years. The doctoral researcher will present work at local and international conferences and participate actively in the Molecular Modelling and Engineering (MME) Group and departmental research activities. For enquiries, contact Prof. Matteo Salvalaglio ([email protected]). Project Description PRIME-LEAP (“Next-generation intensified chemical processes integrating plasma and single-atom catalysis”) is a European research and training network funded by the Marie Skłodowska-Curie Actions. It unites leading universities, research centres, and industrial partners to develop electrified, sustainable chemical processes. The programme targets one of the grand challenges in modern chemistry: the sustainable conversion of methane. Methane, a key component of natural gas and a by-product of steam cracking, represents a vast yet underused feedstock. PRIME-LEAP explores how plasma activation and advanced catalysis can transform methane into value-added products, contributing to Europe’s climate and energy transition goals. Doctoral candidates across the consortium will receive world-class interdisciplinary training in plasma science, catalysis, digital process control, and sustainability assessment. The network combines academic excellence with industrial engagement, fostering a new generation of scientists equipped to design the next wave of green chemical technologies. At UCL, the recruited PhD candidate will focus on computational physical chemistry, using AI and molecular simulations to uncover microscopic mechanisms governing plasma-driven reactions. The project, supervised by Prof. Matteo Salvalaglio, will leverage machine learning to model complex reactive events and enable predictive insights into plasma chemistry. The successful candidate will also participate in international secondments within the consortium, gaining experience in complementary experimental and computational environments. Candidate Profile Applicants should hold (or be close to completing) an excellent first degree in Chemical Engineering, Chemistry, Physics, Computational Science, or a related discipline. Strong analytical skills and motivation for independent research are essential. Desirable experience includes: Knowledge of physical chemistry and molecular simulation methods Familiarity with machine learning techniques and programming Experience with UNIX-based operating systems Eligibility (Marie Skłodowska-Curie Requirements) Candidates must not already hold a doctoral degree. At the time of recruitment, candidates must not have resided or carried out their main activities (work or study) in the UK for more than 12 months within the 3 years prior to the start date. All nationalities and genders are eligible. Candidates must be willing to undertake international mobility, including secondments abroad (up to 30% of the project duration). How to Apply Apply via the UCL application portal: Please nominate Prof. Matteo Salvalaglio as your supervisor and include a short statement of interest. For informal enquiries, email [email protected]. Further details on the MPhil/PhD programme and admissions process are available at: