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Gabriele Sosso

Top university

10 months ago

PhD Studentship – Machine Learning for Organic Materials: From Molecules to Mobility University of Warwick in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Warwick

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Keywords

Computer Science
Data Science
Machine Learning
Chemistry
Materials Science
Mathematics
Molecular Dynamics
Polymer Chemistry
Computational Physics
Monte Carlo Simulation
Multiscale Modeling
Physics

About this position

[Awards for UK, EU, and International applicants cover full University fees, a research training budget, and a tax-free stipend of £20,780 for 2025/26 (standard UKRI rate).]

PhD Studentship – Machine Learning for Organic Materials: From Molecules to Mobility

The University of Warwick is offering a fully funded PhD studentship within the HetSys Centre for Doctoral Training in Modelling of Heterogeneous Systems. This interdisciplinary project, supervised by Professor Gabriele Sosso, aims to advance the understanding of gas transport in organic materials such as polymers, with applications ranging from fuel cells to battery technology. The research will focus on developing machine learning models trained on quantum-level data to simulate molecular interactions and ageing processes, bridging the gap between atomistic simulations and continuum models through robust multiscale approaches.

Students will work on gas/polymer systems relevant to AWE-NST, a UK stakeholder committed to fundamental science with practical impact. The HetSys programme provides a collaborative and vibrant research environment, bringing together expertise from physics, engineering, computer science, and mathematics. Students will gain interdisciplinary training, develop versatile skills in modelling, simulation, and data science, and engage with leading researchers and industry partners.

Funding: The studentship covers full University fees for UK, EU, and International applicants, a research training budget, and a tax-free stipend of £20,780 for 2025/26 (standard UKRI rate). This support ensures students can focus on their research and professional development.

Eligibility: Applicants should have or expect to obtain a first-class or upper second-class degree in a relevant discipline such as physics, chemistry, materials science, engineering, mathematics, or computer science. Experience or interest in computational modelling, simulation, or machine learning is highly desirable. International applicants may need to provide proof of English language proficiency.

Application Process: Applications are open until 28 January 2026. Interested candidates should apply via the HetSys project page, preparing their academic transcripts, CV, and a statement of interest. The HetSys Centre offers guidance and support throughout the application process.

This studentship is ideal for candidates passionate about using advanced computational techniques to solve real-world problems in materials science and energy technology. Graduates of HetSys are equipped for impactful careers in research, technology, and industry.

Funding details

Available

What's required

Applicants should hold or expect to obtain a first-class or upper second-class undergraduate degree (or equivalent) in physics, chemistry, materials science, engineering, mathematics, computer science, or a related discipline. Experience or strong interest in computational modelling, simulation, or machine learning is highly desirable. International applicants may need to provide evidence of English language proficiency (e.g., IELTS or TOEFL).

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Professors

Professor

University Name
Country flag

United Kingdom

Research Interests

Polymer Chemistry

Statistics

Machine Learning

Mathematics

Computer Science