PhD Studentship: High-Throughput Modelling of Crystallisation Processes with Molecular Dynamics

Closing date: Friday, April 12, 2024

Stipend: c. £20,000 (in line with the UCL rate) + UK/Overseas fees

Duration of Studentship: 3 years fees and 3.5 years stipend

Start date: June 2024 

Vacancy information

The Department of Chemical Engineering at University College London (UCL) is seeking an enthusiastic graduate student to work on the development of computational methods to study nucleation, crystal growth and polymorph selection within the context of the ERC Consolidator Project ht-MATTER - High Throughput Modelling of Molecular Crystals out of Equilibrium. The appointment is for 3.5 years. The candidate is expected to carry out research pertaining to the doctoral project, present her/his work in local and international meetings, as well as taking part in the academic activities of the Molecular Modelling and Engineering (MME) Group and of the Chemical Engineering Department.

Studentship description

Molecular crystals (MCs) are found in many everyday products, from food to pharmaceuticals, hiding in plain sight characteristics that make them ideal materials for cutting-edge technological applications. Like construction bricks, MCs’ building blocks can reversibly self-assemble into a plurality of structures, thus distinguishing the chemical properties of building blocks from the physical and mechanical material properties. These characteristics open up endless possibilities in material design, with applications in pharmaceutical manufacturing, separations, catalysis, and organic electronics. Tailoring the composition of the liquid phase in which MCs assemble holds the key to designing processes able to yield materials with desired properties. However, current approaches at MCs computational design are centred on predicting the thermodynamic stability of bulk phases. This paradigm had remained essentially unchanged since its inception more than two decades ago, leaving material and process design practices to empiricism. By neglecting the role of assembly kinetics, current computational crystal structure prediction methods cannot identify attainable MC structures and the ideal conditions (i.e. solvent, composition, temperature) to obtain them.

This studentship is focussed on the application and development of state-of-the art computational methods to investigate out-of-equilibrium, kinetics-dominated processes such as nucleation, growth and polymorph selection in molecular systems.

The aim of the project is to enable a systematic introduction of non-equilibrium effects into computational discovery workflows of relevance in the pharmaceutical and fine chemistry industries.

The work will build on recent developments in computational polymorph prediction and nucleation modelling that benefit from synergies between statistical mechanics, machine learning and computational chemistry, and will develop in the context of ht-MATTER (High-throughput modelling of Molecular crystals out-of-equilibrium), a broader ERC/UKRI funded project.

Person specification

The candidate will have or is expected to soon obtain an excellent first degree in Chemical Engineering, Chemistry, Physics, Computational Science or an associated discipline. Prior research experience, together with the ability to analyse, develop and solve open-ended research problems is essential. Desirable qualifications include knowledge in physical chemistry, molecular simulation techniques, programming, and UNIX-based operative systems.

Eligibility

The post is open to UK, EU and overseas students.

Applications should be submitted through: https://evision.ucl.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RRDCENSING01&code2=0035

Please nominate Prof. Matteo Salvalaglio as supervisor and include a statement of interest.

For informal inquiries please contact Prof. Matteo Salvalaglio at: m.salvalaglio@ucl.ac.uk 

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

https://www.ucl.ac.uk/chemical-engineering/study/mphilphd

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