PhD Studentship in Machine Learning and Statistics

RFCSR; Newcastle upon Tyne; On-site; GBP 18,000 - 21,000; Full time

Benefits offered by this job

Full tuition fee coverage

Annual tax-free stipend

Access to research resources

Job summary

Newcastle University in Newcastle upon Tyne, United Kingdom, invites applications for a funded PhD Studentship in Machine Learning and Statistics, offering a chance to undertake advanced doctoral research within a leading academic environment.

The project focuses on developing and applying modern ML and statistical methods to real‑world problems. You will conduct independent research, analyse data, and publish findings at conferences and in journals.

Qualifications

• Applicants should hold a good honours degree (typically 2:1 or above) in 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 should demonstrate strong academic ability and a clear interest in machine learning and statistical research.

Responsibilities

• Conduct independent research on machine learning and statistics.
• Analyse complex datasets and develop novel computational approaches.
• Disseminate findings through publications and conferences.

Skills

Strong quantitative skills

Analytical thinking

Communication skills

Independent & collaborative work

Education

Bachelor’s degree 2:1 in Mathematics / Statistics / CS / Data Science

Master’s degree in a relevant field desirable

Tools

Python

R

Computational modelling

Job description

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.

Eligibility Criteria
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.

Required Expertise/Skills
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.

Salary Details
Funding typically includes full tuition fee coverage and an annual tax-free stipend in line with UKRI rates