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Digital chemistry driven optimisation of catalytic chemical processes


Key facts

Type of research degree
Application deadline
Monday 29 April 2024
Project start date
Tuesday 1 October 2024
Country eligibility
International (open to all nationalities, including the UK)
Competition funded
Source of funding
Doctoral training partnership
Professor Richard Bourne and Professor Thomas Chamberlain
Additional supervisors
Dr Adam Clayton
School of Chemical and Process Engineering, School of Chemistry
<h2 class="heading hide-accessible">Summary</h2>

The discovery of new catalytic systems and the subsequent reduction of the time scale for transfer of these new chemical processes to the point of reliable manufacture and entrance into the market place is critically important to the health of the nation. These processes contain a vast number of potentially critical parameters, making exploration problematic. This is particularly complicated in the context of catalysis, because as well as continuous variables, such as reaction temperature, reaction time, which are typically easier to integrate into algorithmic optimisation approaches, discrete variables, such as metal and/or ligand type, play a pivotal role. To date integration of such parameters into optimisation experiments has been much less explored. <br /> <br /> This project aims to develop a cyber physical platform approach revolutionizing the transfer from laboratory to production of multistep catalytic processes using advanced data-rich and cognitive computing technologies. We will exploit new algorithms based on Bayesian Optimisation for continuous and discrete variables and evolving methodologies for kinetic model determination that merge data analysis and the generation of further experiments. Machine learning software will generate experiment set points delivered through the cloud to automated laboratory platforms. Multiplexed, on line analytic techniques, including HPLC, GC, NMR, MS, IR etc., will enable analysis of reactions to inform further experiments, thus generating a data generation - data analysis closed-loop. This enables the application of machine learning to chemical development: the system will continuously learn, increasing in confidence and knowledge over time, from previous iterations. <br /> <br /> Note: Position may be filled before close date and recruitment closed.

<h2 class="heading hide-accessible">Full description</h2>

<p class="paragraph" style="text-align:justify">This project has two key objectives, each with its own significant academic research challenge:&nbsp;</p> <p>(i) Develop novel procedures for the self-optimisation of multi-step and continuous flow processes (see <a href="" target="_blank"></a> for an example of our previous work in this area). Machine learning techniques will be coupled with online multipoint analysis to rapidly explore complex interactions between catalytic steps.&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>(ii) Design new multi-step reactor configurations for the telescoping of catalytic steps. Catalytic reactions will be investigated under continuous flow conditions, and different types of catalysts compartmentalised to enable operation at divergent reaction conditions.&nbsp;</p> <p>Research areas (i) and (ii) will be coupled to enable integration of different types of catalysts within a synthetic pathway, and the technology demonstrated towards the synthesis of pharmaceutically relevant compounds. This work will be conducted within the Institute of Process Research and Development (<a href="" target="_blank"></a>).&nbsp;</p>

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

<p style="margin-bottom:11px">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>EPSRC DTP Engineering &amp; Physical Sciences</strong></em> (if you do not apply to this programme code, your application will not be considered) and in the research information section&nbsp;that the research degree you wish to be considered for is&nbsp;<em><strong>Digital chemistry driven optimisation of catalytic chemical processes</strong></em>&nbsp;as well as <a href="">Dr Thomas Chamberlain</a>, <a href="">Professor Richard Bourne</a> and <a href="">Dr Adam Clayton</a>&nbsp;as your proposed supervisors. Please state in the Finance section that the funding source you are applying for is <em><strong>EPSRC Doctoral Training Partnership 2024/25: Chemistry</strong></em>.</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>Applications will be considered after the closing date. &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 3 April 2024 for Leeds Opportunity Research Scholarship, 8 April 2024 for Leeds Doctoral Scholarship or 29 April 2024 for EPSRC DTP:</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> </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><strong>UK Only</strong></p> <p>A highly competitive EPSRC Doctoral Training Partnership Studentship offering the award of fees, together with a tax-free maintenance grant (currently &pound;18,622 for academic session 2023/24) for 3.5 years.&nbsp; Training and support will also be provided.</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>The&nbsp;<a href="">Leeds Doctoral Scholarships</a> and <a href="">Leeds Opportunity Research Scholarship</a> are available to UK applicants (open from October 2023). <a href="">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p>Please refer to the&nbsp;<a href="">UKCISA</a>&nbsp;website for&nbsp;information regarding Fee Status for Non-UK Nationals.</p> <p><em><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></em></p> <p><strong>Non-UK</strong> &ndash;The&nbsp;<a href="">China Scholarship Council - University of Leeds Scholarship</a>&nbsp;is available to nationals of China (now closed for 2024/25 entry). The&nbsp;<a href="">Leeds Marshall Scholarship</a>&nbsp;is available to support US citizens. <a href="">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Important:</strong>&nbsp; Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are <em><strong>not</strong></em> covered under these studentships.</p> <p>Please refer to the <a href="">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals.</p>

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

<p style="margin-bottom:11px">For further information about this project, please contact Dr Thomas Chamberlain by email to&nbsp;<a href=""></a></p> <p>For further information about your application, please contact Doctoral College Admissions by email to <a href=""></a></p>

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