PhD Research Studentships

AI and Machine Learning in Tomography and Electron Microscopy Image Analysis

Supervisor: Roberto VOLPE
Apply by:29 January 2025
Start in:September (Semester 1)

Description

This research project is dedicated to developing cutting-edge image processing techniques to support the analysis and design of porous materials for sustainable applications. Your work will be dedicated to AI-Enhanced Imaging of Porous Materials. During your studentship you will develop machine learning models to analyze synchrotron-based in-situ and in-operando X-ray computed micro-, nano-tomography and Electron microscopy data, improving the structural understanding of porous materials and their functionalities in critical sustainability areas such as water purification, biofuel production, and catalysis.  The work will be conducted in an interdisciplinary team of experts in thermochemical reactions, materials chemistry and advanced synchrotron-based imaging experiments. 

Funding

Funded by: China Scholarship Council
Candidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Roberto VOLPE.

Apply

Start an application for this studentship and for entry onto the PhD Chemical Engineering full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-632" to associate your application with this studentship opportunity.

Related website:https://www.sems.qmul.ac.uk/staff/r.volpe/
Keywords:Artificial Intelligence, Data Science, Machine Learning, Chemical Engineering, Mechanical Engineering, Thermodynamics, Materials Science - Other