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Research Studentship in Thermal Propulsion Systems Group

Research Studentship in Thermal Propulsion Systems Group

3.5-year D.Phil. studentship 

Project: Solidification of cryogenic fluids for energy and transportation applications

Supervisors: Dr Konstantina Vogiatzaki

Cryogenic processes are the core technology of various applications, currently under development in order to tackle grand challenges in advanced healthcare (cryo-surgery is a less invasive -in comparison to other surgical procedures- treatment of cancer tumours), energy sustainability (cryogenic energy storage contributes to harness renewables for carbon-neutral refrigeration and power supply), space exploration (cryogenic O2 (LO2) and H2 (LH2) are used in rocket engines) and cooling (liquid nitrogen (LN2) and liquid helium (LHe) are used to cool superconducting magnets of MRI). Due to the ultra low temperatures during cryogenic processes,  solidification is a phenomenon commonly occuring either as part of the process (such as the solidification of CO2 in carbon capture systems) or unintentionally due to system failure (such as the air freezing when LH2 is accidentally leaked)

Until now new technological developments in the cryogenic field relied solely on experiments. However, performing lab experiments with all the possible combinations of fluids and conditions to determine the optimum operability manifold is very expensive and not always accurate, mainly because of the limitations of experimental techniques, safety issues relating to handling of cryogenic fluids, and lack of experimental equipment that can be operated in very low temperatures. Simulation tools have the potential to reduce the dependency on the experiments and increase our understanding of cryogenic physics in a cost and time effective manner. Unfortunately, regardless of the vast progress in terms of virtual design tools tailored for ultra-high temperature processes (combustion) in engines and gas turbines, robust numerical tools specifically designed for ultra-low temperature conditions do not currently exist.

This project aims to develop a novel computational framework combining CFD, Molecular Dynamics and ML techniques for the development of accurate and cost-effective modelling tools of the solidification processes taking place in ultra-low temperatures, starting from molecular scale information to describe large-scale process. This can help researchers and industry to tackle two of the major challenges in the field of phase transitions: 1) combining traditional methodologies with new data-driven approaches deriving robust macroscopic models based on molecular dynamics; 2) extending the applicability range that will allow calibration of the models to a wider range of conditions in a cost-effective manner.

This project is an excellent opportunity to undertake fundamental research in the field of multiphase flows, involving elements of the rapidly evolving field of Machine Learning.


This studentship is open to Home students (full award – home fees plus stipend). Full details of the eligibility requirements can be found on the UK Research and Innovation website.

Award Value

Course fees are covered at the level set for Home students. The stipend (tax-free maintenance grant) is the UKRI minimum stipend.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

  • A first class honours degree in Engineering, Physics or Computer Science
  • Excellent English written and spoken communication skills

The following skills are also highly desirable:

  • Programming experience (i.e. Matlab, Python,C++, TensorFlow etc.)
  • Strong interest in code development, high performance computing and machine learning
  • Good Knowledge of commercial CFD softwares (such as OpenFOAM, FLUENT, CONVERGE etc)
  • Ability to work within specific deadlines

Application Procedure

Informal enquiries are encouraged and should be addressed to Prof Konstantina Vogiatzaki (

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.  Details are available on the course page of the University website.

Please quote 24ENGMM_KV all correspondence and in your graduate application.

Application deadline: 1st of Dec 2023

Start date: October 2024