Aerospace Engineering (light) PhD Projects, Programmes & Scholarships

We have 7 Aerospace Engineering (light) PhD Projects, Programmes & Scholarships

ZENITH PhD Project: Hydrodynamic and thermal performance of liquid hydrogen in cryogenic tanks

University of Bath Department of Chemical Engineering

The Department of Chemical Engineering at the University of Bath is inviting applications for this funded PhD project expected to commence in September 2024. Read more

Supervisors: Prof J Chew, Dr C Moreno, Dr ATR Rhead

30 May 2024 PhD Research Project Funded PhD Project (Students Worldwide)

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Development of solar-powered self-healing 3D printed composite structures

University of Edinburgh School of Engineering

Development of solar-powered self-healing 3D printed composite structures. 4D printed devices are Additive Manufactured components with shape-shifting capabilities [1]. Read more

Supervisor: Dr F Martinez-Hergueta

30 April 2024 PhD Research Project Funded PhD Project (European/UK Students Only)

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Thermally driven flows in solidification processes

University of Strathclyde Department of Mechanical and Aerospace Engineering

PROJECT SUMMARY (a short summary - max 40 words). With this project, we propose a numerical investigation into a variety of dynamics and effects produced by the interaction of an advancing solidification front with thermally-driven convection in the melt. Read more

Supervisor: Dr M Lappa

Year round applications PhD Research Project Self-Funded PhD Students Only

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Hollow core optical fibres and Radio Frequency signals

University of Southampton Faculty of Engineering and Physical Sciences

Supervisory Team: Radan Slavik, Francesco Poletti, Meng Ding. Project description. Read more

Supervisor: Prof R Slavik

Year round applications PhD Research Project Competition Funded PhD Project (Students Worldwide)

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Concept Mission Design for Hex-Sats to detect biological agents from VLEO

University of Southampton Faculty of Engineering and Physical Sciences

Supervisory Team: Dr Alexander Wittig, Dr Minkwan Kim. Project description. In this PhD, we will develop a complete mission concept for satellites to detect the release of biological agents on the ground through constant monitoring from space. Read more

Supervisor: Dr A Wittig

31 August 2024 PhD Research Project Competition Funded PhD Project (UK Students Only)

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Fur and Feathers: colour, structure and flow control

The University of Manchester Department of Mechanical, Aerospace and Civil Engineering

The objective in this exciting cross-disciplinary project is to investigate the potential of a bio-inspired coating of flexible devices to passively modify energetic modes of an unsteady crossflow and to assess, for the first time, the role of colour in determining mechanical properties. Read more

Supervisor: Dr A Revell

Year round applications PhD Research Project Funded PhD Project (Students Worldwide)

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Synchrotron X-ray inline monitoring of Laser Additive Manufacturing processes using a Machine Learning approach

RMIT University School of Engineering

Laser additive manufacturing (LAM; laser 3D printing) is a key underpinning technology for the digital revolution (Industry 4.0), producing complex objects directly from 3D CAD drawings. Read more

Supervisors: Dr Y Chen, Dr A Rack

Year round applications PhD Research Project Competition Funded PhD Project (Students Worldwide)

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We have 7 Aerospace Engineering (light) PhD Projects, Programmes & Scholarships

Aerospace Engineering (light) PhD Projects, Programmes & Scholarships

We have 7 Aerospace Engineering (light) PhD Projects, Programmes & Scholarships

ZENITH PhD Project: Hydrodynamic and thermal performance of liquid hydrogen in cryogenic tanks

Development of solar-powered self-healing 3D printed composite structures

Thermally driven flows in solidification processes

Hollow core optical fibres and Radio Frequency signals

Concept Mission Design for Hex-Sats to detect biological agents from VLEO

Fur and Feathers: colour, structure and flow control

Synchrotron X-ray inline monitoring of Laser Additive Manufacturing processes using a Machine Learning approach

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