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    <title>Jobs at the University of Leeds | School of Chemical &amp; Process Engineering</title>
    <link>https://jobs.leeds.ac.uk/Vacancies.aspx?cat=756&amp;type=5</link>
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          <title><![CDATA[Research Fellow in Digital Chemistry and Engineering (EPSPE1127)]]></title>
          <link>https://jobs.leeds.ac.uk/rss/click.aspx?ref=EPSPE1127</link>
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            <p id="isPasted"><strong>Are you an ambitious researcher who wants to translate cutting‑edge reaction engineering and automation into real-world products? Are you an ambitious researcher who wants to pioneer the next generation of robotic, reconfigurable chemical reactors for real world impact? Do you want to further your career in one of the UK&rsquo;s leading research-intensive Universities?</strong></p><p>We are seeking a Research Fellow in Reaction Automation to join the EPSRC funded programme R4PID: Reconfigurable, Robotic &amp; Responsive Reactors for Processes through Intensified Development&mdash;a flagship project aiming to redefine how synthetic routes are designed, optimised, and prepared for pharmaceutical manufacture.</p><p>R4PID will develop digitally integrated, microvolume, reconfigurable robotic flow reactors capable of autonomously adapting to the needs of diverse synthetic reactions.&nbsp;</p><p>These systems will:</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Generate microvolume reaction pulses with individually controlled conditions;</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Parallelise droplet based microreactor environments for massively increased throughput based microreactor environments for massively increased throughput;</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Integrate advanced inline sensors (e.g., IR, MS, NMR, UV&ndash;vis) for real time data acquisition time data acquisition;</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Connect to AI driven optimisation and process modelling tools driven optimisation and process modelling tools;</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Provide manufacturing quality process data using micro and nanomole quantities quality process data using micro &nbsp;and nanomole quantities;</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Enable autonomous exploration of discrete variables (catalysts, solvents, reagents);</p><p>&bull;<span style="white-space:pre;">&nbsp;</span>Build a continuous data pipeline from screening &rarr; optimisation &rarr; scale up.</p><p><em>We are open to discussing flexible working arrangements.</em></p><p><br></p><p id="isPasted"><strong>To explore the post further or for any queries you may have, please contact:&nbsp;</strong></p><p><a href="https://eps.leeds.ac.uk/chemistry-process-research-development/staff/4206/prof-richard-bourne">Professor Richard Bourne</a>, Professor of Digital Chemical Engineering</p><p>Email:&nbsp;<a href="mailto:R.A.Bourne@leeds.ac.uk">R.A.Bourne@leeds.ac.uk</a></p><p><br></p><p id="isPasted">Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information, please visit <a href="https://www.gov.uk/skilled-worker-visa">the Government&rsquo;s Skilled Worker visa page.</a></p><p>For research and academic posts, we will consider eligibility under the Global Talent visa. For more information, please visit <a href="https://www.gov.uk/global-talent">the Government&rsquo;s page, Apply for the Global Talent visa.</a></p><p><em>&nbsp;</em></p>
            <p>
              Closing Date: 26 May 2026<br />
            </p>
            <p>
              Section: Research
            </p>
            <p>Salary: &#163;41,064 to &#163;48,822 p.a.</p>
          ]]></description>
          <category><![CDATA[Research]]></category>
          <pubDate>Tue, 12 May 2026 00:00:00 GMT</pubDate>
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