PhD in Modelling carbon using machine learning

For PhD in Modelling carbon using machine learning, tuition is 25,100 GBP per year, while applications for the Sep 2027 intake close on Mar 1, 2027.

The PhD in Modelling carbon using machine learning at Loughborough University is a 3-year program for students with a Master's degree. It helps you develop skills in machine learning and atomic modelling to study carbon materials.

The curriculum covers project details, carbon materials, and machine learning techniques. You will learn to use large scale atomistic modelling and atomic cluster expansion descriptors to study properties of carbon materials in high temperature environments.

After completing this program, you can work as a Research Scientist, Materials Engineer, or Computational Modeller in industries like energy, aerospace, or automotive. You can also work with companies like EDF or in research institutions.

Loughborough University presents a learner-focused environment with extensive academic and campus resources tailored to international students. The institution highlights modern campus facilities, strong research and teaching support, and a wide-ranging library collection that supports coursework and independent study. Students benefit from well-equipped laboratories, collaborative study spaces and a library designed to meet the demands of diverse academic programs.

The university promotes a vibrant campus life through many clubs, societies and sports opportunities, encouraging students to balance academic work with extracurricular engagement. Student organizations cover arts, entrepreneurship, sports and cultural exchange, providing platforms for leadership, networking and social integration. On-campus catering, leisure facilities and landscaped areas create a welcoming atmosphere for study and relaxation.

International opportunities and partnerships enhance global mobility and employability, with pathways for study abroad, industry links and internship experiences that connect students with multinational employers. Teaching is delivered in modern facilities across multiple campuses, and student services support orientation, accommodation and academic success. Overall, this university aims to combine strong academic provision with an active campus community to prepare graduates for global careers.