13 Master scholarships at Cranfield University

The hybridity of polluted freshwaters - PhD

, Rest of world Reference numberSWEE0248 Entry requirements An ideal candidate for this position will have a first or second class UK honors and Masters degree in Natural Resource Management, Anthropology

Integrated indicators of ecological health for rivers based on riverbed biofilms - PhD

years. In total the award will fund up to 18 full time PhD Scholarships, including three scholarships for international applicants, 12 home (UK) PhD scholarships, and three Master's plus PhD scholarships

Future Aircraft Communications and Data Management for Flight Dynamics Predications PhD

connectivity and flight dynamics, incorporating Artificial Intelligence (AI) and Machine Learning (ML) to develop innovative prediction mechanisms. The primary goal of this project is to design advanced

Aero-Engine Nacelle Aerodynamics And Optimisation PhD

aerodynamic characteristics associated with the propulsion system integration. This can apply to the aero-engine intake, exhaust, nacelle and main propulsion system. The overall aim of the funded PhD project is

Developing Ontologies for Digital Engineering and Manufacturing PhD

and effective framework development. The main outcomes encompass feedback and reflection on the ontology performance, scalability, reusability and enhanced FAIR evaluation. Cranfield University is

SENSS DTP Student led studentships

receive financial support to do a Masters as well as your PhD. What is Cranfield looking for? We are looking to hear from students who want to work on the following topics. At a glance Application

Design and Assessment of Carbon Fibre Composite Joints PhD

controls to the manufacturing procedure and environment, joint design, inclusion of some surface modification and control of the adhesive cure cycle. The primary aim of this project is to assess

Actuator PHM exploiting multi-physics digital twin (DT) and machine learning (ML) PhD

, and reliable operation in diverse environments. This involves two main goals: 1) Optimisation of the Battery Management System (BMS): The aim is to implement an accurate BMS that effectively monitors

CFD-FEA Combined Thermal-Fluid-Mechanical Modelling for Defect Control in Additive Manufacturing PhD

manufacturing, specifically focused on directed energy deposition process utilising metal wire as the primary feedstock. Within this exciting realm, through CFD-FEA combined thermal-fluid-mechanical modelling, we

Framework for Manufacturing Prognostics PhD

cities of Oxford and Cambridge. Our central location provides easy access from the M1, excellent main line rail service as well as proximity to key international airports. Set in rolling countryside