PhD Studentship in Machine Learning and Statistics

PhD Studentship in Machine Learning and Statistics

Newcastle University Newcastle upon Tyne, United Kingdom

Newcastle University is offering a funded PhD studentship in Machine Learning and Statistics, providing an opportunity to undertake advanced doctoral research within a leading academic environment. This studentship is aligned with the university’s commitment to excellence in data science, artificial intelligence, and statistical modelling, and is hosted within a vibrant research community that supports interdisciplinary collaboration and innovation.

The project focuses on the development and application of modern machine learning and statistical methodologies to address complex, real‑world problems. The successful candidate will engage in high‑quality research, working closely with academic supervisors and contributing to ongoing research initiatives within the institution. Responsibilities include conducting independent research, analysing complex datasets, developing novel computational approaches, and disseminating findings through publications and conferences.

The studentship offers comprehensive academic support, access to advanced computational resources, and opportunities for professional development. The candidate will become part of a dynamic postgraduate research community and will be encouraged to engage in knowledge exchange and collaborative activities across disciplines.

Applicants should hold, or expect to obtain, a good honours degree (typically a 2:1 or above) in a relevant subject such as Mathematics, Statistics, Computer Science, Data Science, or a closely related discipline. A master’s degree in a relevant field is desirable but not essential. Candidates must demonstrate strong academic ability and a clear interest in machine learning and statistical research.

Strong quantitative and analytical skills, with a solid foundation in mathematics and statistics. Experience with programming languages such as Python, R, or similar is highly desirable. Familiarity with machine learning techniques, data analysis, and computational modelling is advantageous. Candidates should possess strong problem‑solving abilities, effective communication skills, and the capacity to work both independently and collaboratively within a research environment.

Funding typically includes full tuition fee coverage and an annual tax‑free stipend in line with UKRI rates.