or
Looking to list your PhD opportunities? Log in here.
Distillation is one of the most commonly applied unit operations in the process industry, with significant capital and operation costs. Even though systematic methods and procedures have been established for distillation design, conventional design approach for distillation systems still relies heavily on engineers' knowledge and experience, even if a design task for the same type of distillation unit has been done many times before. This research aims to develop a smart design method, using machine learning, in order to minimise the requirement of engineers' involvement in the design process, which can improve the design quality and work efficiency.
Eligibility
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.
Funding
At Manchester we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers applying for competition and self-funded projects.
For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.
Before you apply
We strongly recommend that you contact the supervisor(s) for this project before you apply.
How to apply
Apply online through our website: https://uom.link/pgr-apply-fap
When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.
Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.
After you have applied you will be asked to upload the following supporting documents:
If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.
We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
The university will respond to you directly. You will have a FindAPhD account to view your sent enquiries and receive email alerts with new PhD opportunities and guidance to help you choose the right programme.
Log in to save time sending your enquiry and view previously sent enquiries
The information you submit to The University of Manchester will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Manchester, United Kingdom
Start a New search with our database of over 4,000 PhDs
Based on your current search criteria we thought you might be interested in these.
Rolls-Royce sponsored PhD Scholarship, Design and Simulation of Stiffness-Adjustable Robotic Systems for Performing on-Wing Repair of Aero-Engines - (ENG 192)
University of Nottingham
Smart Computer Models for Nuclear Reactor Design
University of Sheffield
Modelling, design and testing of integrated anaerobic digestion and hydroponics systems for closed-loop urban applications
University of Sheffield