Computational Materials and Molecular Sciences
The Computational Materials and Molecular Science group provides expertise in modelling materials and their properties to help interpret experimental data, gain important insights and to design new experiments and materials. This expertise is increasingly important in areas such as autonomous discovery which iterates the loop from atomistic models of properties to material creation, measurement and improvement.
Supporting and advancing experimental data analysis
To impact experimental science we:
- Provide platforms and interfaces to access advanced tools and workflows
- Provide community–focused development, maintenance and training in sustainable software for molecular and materials physics and chemistry
- Develop multiscale and multi-physics simulation techniques to model chemical and physical processes in realistic conditions and compare to experimental data
- Harness the potential of artificial intelligence to support materials and molecular science and lower barriers to entry
- Make computational intensive models accessible to experimentalists through the use of surrogate models – for example in spectroscopy and laser pump-probe experiments
- Machine learned models to support structural refinement with experimental data
- Use of large language models to help novice or non-experts interact with, and use use of advanced modelling tools
- Enable reproducible workflows and open science in materials science using FAIR data principles
The group currently contains over 40 people with an expertise spanning across materials and molecular modelling.
- Atomistic models to understand optimal structural configurations
- Properties from averages over atomistic configurations (thermodynamic properties, or pair distribution functions )
- Vibrational properties (phonons) and related spectroscopies
- Material properties such as conductivity, optical behaviours such as emissions or lifetimes, and overall function from electronic band structure calculations
- Electronic and nuclear response functions and related spectroscopies
- Light-matter (molecule, atom) interactions, to understand, dynamics and reactivity or spectroscopic measurements.
FAQs
What do we offer?
The Ada Lovelace Centre will fund 50% of the cost of a studentship (fees and stipend) with a partner University.
What is the Ada Lovelace Centre?
The Ada Lovelace Centre is a collaborative hub that helps UK science facilities use computing to solve complex research challenges. It brings together experts in data, software, and artificial intelligence to accelerate scientific progress.
Who can apply?
Any academic belonging to a UK university with the authorisation to supervise PhD students may apply as the university supervisor.
What are the terms of the funding?
The student is expected to spend a significant portion of their time (30-50%) with Ada Lovelace Centre teams and working with facilities during their PhD. In practice, this is typically arranged as a block of time, typically in year 2, spent with the Ada Lovelace Centre supervisors.
The aim of the studentships is to support forward looking developments and to build both the links between facilities and Ada Lovelace Centre and the wider expertise which supports our goals. This therefore requires that the PhD supervision is not simply between a University and a facility but links strongly to the scientific computing expertise in the Ada Lovelace Centre.
