Exit Menu

Machine Learning in Modelling, Optimisation and Experimental Validation of Post-Combustion CO2 Capture with Novel Adsorbents

Brunel University London (BUL) is recruiting to EPSRC Doctoral Training Partnership (DTP) PhD studentships effective 1 October 2020. Applications are invited for the following specific project called “Machine Learning in Modelling, Optimisation and Experimental Validation of Post-Combustion CO2 Capture with Novel Adsorbents”. Successful applicants will receive an annual stipend (bursary) of £17,285 plus payment of their full-time home tuition fees for a period of 36 months (3 years).  Applicants must be eligible for home tuition fees either through nationality, residency (living in the UK for at least three years and not wholly for educational purposes) or other connection to the UK. 

The successful applicants will join the internationally recognised researchers in the Department of Chemical Engineering. This exciting research project is focused on developing and experimentally validating robust machine learning algorithms, capable of optimising an adsorption-based CO2 capture process based on the novel adsorbents developed and experimentally tested in our research labs.  Machine learning comprises multifaceted tools to effectively model and predict complex and highly non-linear processes. Its use is a practical method in successful optimisation of CO2 capture processes, which are highly non-linear by nature.  This project will be a comprehensive extension to an existing experimental research in our group on developing new adsorbents; it strives to pave the way for accelerated deployment of CCS by helping the UK to meet its recently-announced target of zero greenhouse gas emissions in the country by 2050.

Applicants will be required to demonstrate their ability to understand and apply sound engineering principles. Positive engagement with those in the research group and an enthusiastic ability to communicate, analyse and solve problematic situations whilst maintaining a high-level of motivation will be of utmost importance.

Please contact Dr Salman Masoudi Soltani at salman.MasoudiSoltani@brunel.ac.uk  for an informal discussion about the studentship.

This is a College of Engineering, Design and Physical Sciences: EPSRC Funded DTP PhD Studentship.


Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage. 

Experience in applying engineering principles to analyse/synthesise chemical processes. Some working experience with MATLAB and/or Artificial Neural Networks is an advantage.  In addition, applicants should be highly motivated, able to work independently as well as part of a team, collaborate with others and have good communication skills.

How to apply

Please submit your application documents (see list below) by Noon on Friday 26 June 2020 to cedps-pgr-office@brunel.ac.uk. Interviews will take place in July 2020.

  • Your up-to-date CV;
  • Your personal statement (300 to 500 words) summarising your background, skills and experience;
  • Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s);
  • Evidence of your English language skills to IELTS 6.5 (or equivalent, 6.0 in all sections), if appropriate;
  • Contact details for TWO referees, one of which can be an academic member of staff in the College.

Remember to state the title of the project at the top of your personal statement.