利物浦大学PhD Position in Guaranteed Structure Prediction with Machine Learning申请条件要求-申请方
主办方
利物浦大学
PhD直招介绍
About the Project
New materials are urgently needed to address global challenges our society faces today. The atomistic structure dictates their stability and properties. Structure prediction is difficult due to the quantum nature of interatomic interactions and the combinatorial explosion of possible arrangements of atoms. Classical force-fields and heuristic optimisation methods are typically used to overcome these challenges.
In a recent breakthrough [1], we developed a mathematical optimisation approach based on integer programming to structure prediction that provides guaranteed outcomes and offers new ways of addressing combinatorial explosion. However, it relies on force-fields for predictions, which are often chemistry specific and have limited fidelity. Recently, interatomic potentials based on machine learning have emerged as the main avenue to address these issues.
In this project, we will expand our approach and make machine learning part of the optimisation routine. This includes simultaneous use of interatomic interaction and property prediction models. High-fidelity assessment of stability and properties with guarantees across the periodic table will provide a unique capability in material science. The student will contribute to trustworthy and verifiable AI in science and gain transferable skills in combining machine learning with optimisation. The project is multi-disciplinary, and we specifically welcome students with backgrounds in mathematics, physics, chemistry, engineering, and computer science.
The global need for researchers with capabilities in materials chemistry, digital intelligence and automation is intensifying because of the growing challenge posed by Net Zero and the need for high-performance materials across multiple sectors. The disruptive nature of recent advances in artificial intelligence (AI), robotics, and emerging quantum computing offers timely and exciting opportunities for PhD graduates with these skills to make a transformative impact on both R&D and society more broadly.
The University of Liverpool EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry( https://www.liverpool.ac.uk/digital-and-automated-materials-chemistry/ ) is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2025. These students will develop core expertise in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme they will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.
This training is based on our decade-long development of shared language and student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory (MIF)( https://www.liverpool.ac.uk/materials-innovation-factory/ ), the largest industry-academia colocation in UK physical science. The training content has been co-developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.
We want all our Staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, if you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.
References
[1] V. V. Gusev et al., Optimality guarantees for crystal structure prediction, Nature 619, 68-72, (2023)
利物浦大学 PhD Position in Guaranteed Structure Prediction with Machine Learning项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
The EPSRC funded Studentship will cover full tuition fees of £4,786 pa. and pay a maintenance grant for 4 years, starting at the UKRI minimum of £19,237 pa. for academic year 2024-2025 (rates for 2025-2026 TBC). The Studentship also comes with a Research Training Support Grant to fund consumables, conference attendance, etc.
EPSRC Studentships are available to any prospective student wishing to apply including both home and international students. While EPSRC funding will not cover international fees, a limited number of scholarships to meet the fee difference will be available to support outstanding international students.
利物浦大学Phd申请条件和要求都有哪些？PhD Position in Guaranteed Structure Prediction with Machine Learning项目是不是全奖？有没有奖学金？下面我们一起看一下利物浦大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
Candidates will have, or be due to obtain, a Master’s Degree or equivalent related to Physical Science, Engineering or Computational Science. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.
报名方式
申请链接
招生人信息
Dr V Gusev
邮箱：Vladimir.Gusev@liverpool.ac.uk
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