PhD Studentship – Lattice Boltzmann Simulations of Boundary Layer Flows over Low-Drag Engineered Surfaces
University of Greenwich
Greenwich, London, United Kingdom
The University of Greenwich is offering a fully funded PhD studentship focused on advanced computational fluid dynamics, specifically investigating lattice Boltzmann simulations of boundary layer flows over low-drag engineered surfaces. This research project aims to enhance understanding of fluid–surface interactions and develop innovative solutions to reduce drag in engineering systems, with potential applications in aerospace, marine, and energy sectors.
The successful candidate will undertake high-level computational research using lattice Boltzmann methods to model and analyse boundary layer behaviour over specially designed surfaces. The project involves developing simulation frameworks, validating models against theoretical or experimental data, and contributing to the advancement of numerical techniques in fluid mechanics. The candidate will work within a supportive academic environment, benefiting from expert supervision, access to high-performance computing facilities, and opportunities for collaboration and dissemination through conferences and publications.
This studentship provides comprehensive training in computational modelling, numerical methods, and fluid dynamics, alongside transferable research and professional skills. The position is full-time and aligned with the University’s commitment to impactful, interdisciplinary research.
Eligibility Criteria
Applicants should hold, or expect to obtain, a good honours degree (at least a UK 2:1 or equivalent) in Mechanical Engineering, Aerospace Engineering, Physics, Mathematics, or a closely related discipline. A Master’s degree in a relevant field is desirable. Candidates must demonstrate a strong background in fluid mechanics and numerical methods.
Required Expertise/Skills
Solid understanding of fluid dynamics and boundary layer theory
Experience or familiarity with computational fluid dynamics (CFD) methods
Programming skills in languages such as Python, C++, or MATLAB
Strong analytical and problem-solving abilities
Ability to work independently and within a research team
Effective written and verbal communication skills
Interest in numerical modelling and high-performance computing
Salary Details
Fully funded studentship including a stipend (in line with UKRI rates) and tuition fee coverage
Application Deadline
Not specified