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PhD Computational Chemistry at Newcastle Univers ... (No replies)
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PhD Computational Chemistry at Newcastle University: Machine Learning Force Fields for Battery Materials (UK/Home students)
Job Ad: https://www.jobs.ac.uk/job/CWO737/phd-studentship-in-computational-chemistry-machine-learning-potentials-for-molecular-materials
Application Deadline: 3rd April 2023
Supervisor: Dr. Ioan-Bogdan Magdău, Lecturer in Computational Chemistry at Newcastle University
We are seeking to recruit a UK/Home applicant for a PhD position at Newcastle University in the field of machine learning (ML) for molecular modelling. This PhD project will develop machine learning inter-atomic potentials (MLIPs) for molecular materials and organic-inorganic interfaces relevant to energy storage technology and medicinal applications.
Project Overview:
Ab initio molecular dynamics (MD) methods are the gold standard for studying molecular mechanisms in the condensed phase, however, they are too expensive to capture many key properties that converge slowly with respect to simulation length and time scales. ML approaches can reproduce the accuracy of ab initio simulation, and are, at the same time, sufficiently affordable to capture the time- and length-scales relevant to experimental measurements.
The efficiency and accuracy of ML models have been thoroughly studied on fixed datasets but the performance of these models in actual MD simulations remains the topic of intense research. Molecular systems are particularly challenging to model owing to a large difference in scale between intra- and inter-molecular interactions.
This studentship will address the following questions:
1) How can we enhance ML techniques to improve the accuracy of inter-molecular interactions in the condensed phase?
2) How can we adapt current active learning protocols to speed up the development of ML models in soft molecular systems?
3) Can we use accurate inter-molecular ML force fields to better understand ion transport in rechargeable batteries? How about drug binding in proteins for medicinal applications?
Through the completion of this PhD, you will develop your scientific expertise in molecular modelling for applications in renewable energy materials, and will improve your skills in computer simulations, ML and data science, in general. We will work in collaboration with Professor Gábor Csányi (University of Cambridge), Dr James Dawson (NUAcT at Newcastle University) and Dr Daniel Cole (UKRI FLF at Newcastle University).