STOR-i Centre for Doctoral Training (CDT) PhD Studentship in Statistics and Operational Research
Lancaster University
Lancaster, United Kingdom
Lancaster University invites applications for fully funded PhD studentships within the STOR-i (Statistics and Operational Research with Industry) Centre for Doctoral Training (CDT). This prestigious doctoral programme offers an integrated four-year PhD combining advanced training in statistics, operational research, and data science with real-world industrial collaboration.
The STOR-i CDT is designed to equip students with cutting-edge analytical, computational, and problem-solving skills, preparing them for impactful careers in academia, industry, and the public sector. The programme begins with a structured first year of taught modules covering core topics such as statistical inference, machine learning, optimisation, and data analysis, followed by three years of focused doctoral research. Students will undertake interdisciplinary research projects co-developed with industry partners, gaining valuable experience in applying theoretical methods to practical challenges.
Participants benefit from a highly collaborative and supportive research environment, working alongside leading academics and industry professionals. The programme includes opportunities for industrial placements, professional development, and engagement with a wide network of partners. Students will also have access to world-class research facilities and training resources, fostering both academic excellence and transferable skills.
Eligibility Criteria:
Applicants should hold, or expect to obtain, a first-class or strong upper second-class honours degree (or international equivalent) in a relevant quantitative discipline such as mathematics, statistics, operational research, engineering, physics, computer science, or a closely related field. Candidates must meet the University’s English language requirements where applicable.
Required expertise/skills:
Candidates should demonstrate strong quantitative and analytical abilities, with a solid foundation in mathematics and/or statistics. Programming skills and experience with data analysis are highly desirable. Applicants should show an interest in interdisciplinary research and the application of quantitative methods to real-world problems. Strong communication skills and the ability to work both independently and collaboratively are essential.
Salary details:
The studentship provides full tuition fees and a tax-free annual stipend in line with UKRI rates, along with additional funding for research training, travel, and industrial placements.
Application Deadline:
Not specified