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Machine Learning Assisted Discovery of Polymeric Materials


Key facts

Type of research degree
Application deadline
Wednesday 31 May 2023
Project start date
Sunday 1 October 2023
Country eligibility
UK only
Competition funded
Source of funding
Doctoral training partnership
Dr Nicholas Warren
School of Chemical and Process Engineering
<h2 class="heading hide-accessible">Summary</h2>

The application of digital technologies is transforming the discovery and manufacturing process within small-molecule chemistry. Our vision is to extend its impact to polymer science where such technologies are yet to be embraced. To achieve this we are seeking to recruit highly motivated PhD candidates to join our team focussed on Artificial Intelligence and Polymer Science. Candidates will employ advanced AI techniques combined with automated reactors to discover new polymers and optimise their synthesis.<br /> <br /> Projects will involve designing and programming a reactors capable of conducting several consecutive polymerisation reactions and automatically analysing the products. The reactor will use machine learning algorithms to direct experimentation, allowing exploration of parameter space which comprise multiple conflicting variables. Within the group, technologies have already been developed which can optimise the synthesis of model polymers (see Polymer Chemistry, 2022, 13, 1576) but a similar approach is now required to develop more applicable materials. <br /> <br /> The project has three main components:<br /> 1) Develop an automated reactor configuration with online monitoring (e.g. benchtop NMR and liquid chromatography) which can conduct multiple polymerisation reactions in quick succession using minimal amounts of material.<br /> 2) Implement the reactor for screening polymer materials comprising multiple monomers for applications in liquid formulations as dispersants, viscosity modifiers or friction reduction agents.<br /> 3) Use machine learning to develop models which can relate the composition of the polymer to its performance. This will guide further experimentation which can either explore the space, or optimise performance based on industrial need.<br /> <br /> There is considerable flexibility in these activities, wherein the candidate may want to focus more on a specific area, plus opportunities to work with overseas collaborators..

<h2 class="heading">How to apply</h2>

<p>Formal applications for research degree study should be made online through the&nbsp;<a href="">University&#39;s website</a>. Please state clearly in the Planned Course of Study section that you are applying for <em><strong>PHD Chemical &amp; Process Engineering FT</strong></em> and in the research information section&nbsp;that the research degree you wish to be considered for is&nbsp;<em><strong>Optimizing Polymer Synthesis using Artificial Intelligence</strong></em> as well as&nbsp;<a href="">Dr Nicholas Warren</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p> <p class="MsoNoSpacing">Applications will be considered on an ongoing basis. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents in support of your application by the closing date of 31 May 2023:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> <li>Funding information:&nbsp;EPSRC Doctoral Training Partnership</li> </ul>

<h2 class="heading heading--sm">Entry requirements</h2>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<h2 class="heading">Funding on offer</h2>

<p class="MsoNoSpacing">A highly competitive EPSRC Doctoral Training Partnership Studentship consisting of the award of fees with a maintenance grant (currently &pound;17,668 for session 2022/23) for 3.5 years.</p> <p>This opportunity is open to UK applicants only.&nbsp; All candidates will be placed into the EPSRC Doctoral Training Partnership Studentship Competition and selection is based on academic merit.</p> <p>Please refer to the&nbsp;<a href="">UKCISA</a>&nbsp;website for&nbsp;information regarding Fee Status for Non-UK Nationals.</p>

<h2 class="heading">Contact details</h2>

<p>For further information about this project, please contact Dr Nicholas Warren<br /> e: <a href=""></a></p> <p>For further information about your application, please contact Doctoral College Admissions<br /> e:&nbsp;<a href=""></a></p>

<h3 class="heading heading--sm">Linked funding opportunities</h3>
<h3 class="heading heading--sm">Linked research areas</h3>