Matteo Salvalaglio

A PhD position is available in the Department of Chemical Engineering at University College London, supervised by Professor Matteo Salvalaglio. The research focuses on computational applied physical chemistry, specifically developing enhanced sampling and free energy methods for computational kinetics in complex environments such as liquids and surfaces. The project will integrate statistical mechanics and machine learning approaches and is supported by a European Union grant, forming part of a broader collaborative effort. Candidates should have a background in chemical engineering, chemistry, physics, or related disciplines, and an interest in computational methods and machine learning. The position is set to begin in January 2026, with further details and the official advertisement forthcoming. Interested applicants are encouraged to contact Professor Salvalaglio for guidance on the application process. More information about the group and contact details can be found on the group website.

A PhD position is available in the Department of Chemical Engineering at University College London, supervised by Professor Matteo Salvalaglio. The research will focus on computational applied physical chemistry, specifically developing enhanced sampling and free energy methods for computational kinetics in complex environments such as liquids and surfaces. The project will integrate statistical mechanics and machine learning approaches and is supported by a European Union grant, forming part of a broader collaborative effort. Candidates should have a strong interest in computational chemistry, physical chemistry, and related fields, with experience or enthusiasm for statistical mechanics and machine learning. The position is set to begin in January 2026. Interested applicants are encouraged to contact Professor Salvalaglio for further details and guidance on the application process. More information about the group and contact details can be found at https://mme-ucl.github.io/contact. Funding is provided by the EU grant, but specific financial details are not disclosed. The official advertisement will be released soon, and candidates should monitor the provided links for updates.

A PhD position is available in the Department of Chemical Engineering at University College London, supervised by Professor Matteo Salvalaglio. The research will focus on computational applied physical chemistry, specifically developing enhanced sampling and free energy methods for computational kinetics in complex environments such as liquids and surfaces. The project will leverage concepts from statistical mechanics and machine learning, and is supported by a European Union grant as part of a broader collaborative effort. Ideal candidates should have a background in chemistry, chemical engineering, physics, or a related discipline, with strong interest and skills in computational methods, statistical mechanics, and machine learning. The position is expected to start in January 2026. Interested applicants are encouraged to contact Professor Salvalaglio for further details and advice on the application process. More information about the group and contact details can be found at https://mme-ucl.github.io/contact. The official advertisement will be published soon.

Coming soon: a fully funded PhD opportunity at University College London in Chemical Engineering , hosted by Professor Matteo Salvalaglio (Molecular Systems Engineering). The project focuses on the development and application of computational methods to understand and predict the behaviour of molecular crystals . Research topics include molecular simulations , molecular dynamics , statistical mechanics , statistical thermodynamics , free energy calculations , crystal polymorphism , phase transitions , nucleation , crystallisation , and machine learning for molecular modelling . The work sits at the interface of chemical engineering, physics, chemistry, materials science, and computational modelling, with applications relevant to the pharmaceutical and materials industries. The aim is to improve the prediction and control of crystal form stability and transformation. Funding is fully provided, including full UK/Home tuition fees and a tax-free stipend at the standard London UKRI rate . Eligible applicants are encouraged to have backgrounds in Chemical Engineering, Physics, Chemistry, Materials Science, Mathematics , or related disciplines. The official advertisement will be released shortly, and prospective candidates may contact the supervisor informally by email in advance.