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University of Strathclyde Maths & Computing PhD Projects, Programs & Scholarships

We have 36 University of Strathclyde Maths & Computing PhD Projects, Programs & Scholarships

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Showing 31 to 36 of 36
  Mathematical Modelling and Analysis of Sessile Droplets
  Prof S K Wilson, Dr A Wray
Applications accepted all year round

Funding Type

PhD Type

The behaviour of sessile droplets is an area of very active international research, with new publications appearing on an almost daily basis and entire conferences now dedicated to the topic.
  Protecting our seas using computers - Modelling and forecasting the expansion of a highly invasive seaweed
  Dr B Chen, Prof M Heath
Applications accepted all year round

Funding Type

PhD Type

This fully-funded 3.5 year studentship will remain open only until filled. We recommend applying immediately. In this project, you will meet with the challenge of developing an individual based model to simulate the growth and dispersal of a highly invasive seaweed (Japanese eelgrass) driven by coastal ocean currents.
  Ultrasonic Imaging of Titanium Alloy Textures
  Dr K Tant
Applications accepted all year round

Funding Type

PhD Type

Applications are invited for a research studentship in the field of ultrasonic non-destructive evaluation (NDE), leading to the award of an Engineering Doctorate (EngD) degree.
  Fluid Dynamic Instabilities and Solid Particle Transport in Thermal Flows
  Dr M Lappa
Applications accepted all year round

Funding Type

PhD Type

With this Ph.D.
  Coarse-Grained Simulation of DNA
  Dr O Henrich
Applications accepted all year round

Funding Type

PhD Type

Funding for a 3.5-year PhD project at the Department of Physics, University of Strathclyde, Glasgow is available from 1 October 2019 for Home/UK/EU students.
  Scalable Qubit Arrays for Quantum Computation and Optimisation
  Dr J Pritchard, Prof E Riis
Applications accepted all year round

Funding Type

PhD Type

Quantum computation offers a revolutionary approach to information processing, providing a route to efficiently solve classically hard problems such as factorisation and optimisation as well as unlocking new applications in material science and quantum chemistry that could in future be scaled up to accelerate drug design or optimised materials for aerospace and manufacturing.
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