<?xml version="1.0" encoding="ISO-8859-1" ?>
<!-- Do not remove, space added for FireFox bug                                                                                                                                                        
                                                                                                                                                                                                       
                                                                                                                                                                                                       -->
<?xml-stylesheet title="XSL_formatting" type="text/xsl" href="/rss/rss.xslt"?>
<rss version="2.0" siteURL="https://jobs.nottingham.ac.uk/" siteName="Jobs at the University of Nottingham" cssPath="/Org/Layout/Css/v23"
  catType="category" catTypes="categories"
  catTitle="Mathematical Sciences" >
  <channel>
    <title>Jobs at the University of Nottingham | Mathematical Sciences</title>
    <link>https://jobs.nottingham.ac.uk/Vacancies.aspx?cat=601&amp;type=5</link>
    <description>Latest job vacancies at University of Nottingham</description>
    
        <item>
          <title><![CDATA[Research Associate/Fellow (Fixed-Term) (SCI269726)]]></title>
          <link>https://jobs.nottingham.ac.uk/rss/click.aspx?ref=SCI269726</link>
          <guid>https://jobs.nottingham.ac.uk/rss/click.aspx?ref=SCI269726</guid>
          <description><![CDATA[
            <p id="isPasted">We are looking for a researcher, whose expertise lies in applied statistical modelling and methods in biological settings, to work with Prof. Gary Mirams and Prof. Simon Preston on an externally-funded project entitled &ldquo;A continually-learning framework for uncertainty quantification and translation of preclinical studies to human cardiovascular safety&rdquo;. The central aim of the project is to develop a statistical decision-support tool that quantifies what each animal cardiovascular-safety study tells us beyond cell and simulation-based tests, flagging studies that are ready for retirement, avoiding unnecessary animal trials.</p><p>We believe that talented and inclusive teams deliver the highest quality research and are seeking applications from high quality candidates who enhance the diversity of our existing team. The School is committed to creating opportunities for people traditionally under- represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.</p><p>You will be able to carry out duties to the highest standard and to evidence how through your experience you will:</p><p>&middot; Undertake original research of international excellence.</p><p>&middot; Develop research objectives and proposals for own and/or collaborative research area.</p><p>&middot; Prepare papers for publication in leading journals and/or contribute to the dissemination at national/international conferences, workshops and meetings resulting in successful research outputs.</p><p>&middot; Identify opportunities and assist in writing bids for research grant applications. Prepare proposals and applications to both external and/or internal bodies for funding purposes.</p><p>We are looking for a confident, organised researcher who can evidence:</p><p>&middot; A PhD, or equivalent, in mathematics, statistics or closely related discipline or near to completion of a PhD</p><p>&middot; Expert knowledge of statistical models and methods, especially in biological and medical settings applied to real-world data.</p><p>&middot; Excellent communication and organisational skills.</p><p>&middot; The ability to work independently and as part of a multidisciplinary and multicultural team.</p><p>This full-time position (36.25 hours weekly) is available from 1st July 2026 [or as soon as possible thereafter] until 31st March 27 . Many of our team have flexible working patterns so we&rsquo;re open to discuss flexible working arrangements with you.</p><p>If it sounds like you would be a good fit, we look forward to hearing from you.</p><p>For information about the School of Mathematical Sciences and active research themes see: http://www.nottingham.ac.uk/mathematics/index.aspx.</p><p>Informal enquiries may be addressed to Prof. Gary Mirams (gary.mirams@nottingham.ac.uk) or Simon Preston (simon.preston@nottingham.ac.uk). Please note that applications sent directly to these email ad dresses will not be accepted.</p><p>To find out more about the People and Culture in the School of Mathematical Sciences please visit our website: https://www.nottingham.ac.uk/mathematics/edi/edi.aspx</p>
            <p>
              Closing Date: 14 Jul 2026<br />
              Category: Research and Teaching (R&T)
            </p>
          ]]></description>
          <category><![CDATA[Research and Teaching (R&amp;T)]]></category>
          <pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate>
        </item>
      
        <item>
          <title><![CDATA[Senior Research Fellow in Cardiac Electrophysiology Modelling (Fixed-term) (SCI177026)]]></title>
          <link>https://jobs.nottingham.ac.uk/rss/click.aspx?ref=SCI177026</link>
          <guid>https://jobs.nottingham.ac.uk/rss/click.aspx?ref=SCI177026</guid>
          <description><![CDATA[
            <p id="isPasted">We are looking for an experienced researcher whose expertise lies in mechanistic cardiac electrophysiology modelling, to work with Prof. Gary Mirams and Prof. Simon Preston on an externally-funded project entitled &ldquo;A continually-learning framework for uncertainty quantification and translation of preclinical studies to human cardiovascular safety&rdquo;. The aim of the project is to develop a statistical decision-support tool that quantifies the accuracy of mechanistic electrophysiology model predictions for drug-induced changes to electrophysiology observed in animal cardiovascular safety studies.</p><p>We believe that our talented and inclusive teams deliver the highest quality research and are seeking applications from quality candidates who enhance the diversity of our existing team. The School is committed to creating opportunities for people traditionally under- represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.</p><p>You will be able to carry out research of a high standard, and evidence, through your experience, how you will undertake original research of international excellence. It will be key that you prepare you work for publication in leading journals, and contribute to its distribution at national and international meetings.</p><p>You will be an organised researcher who can evidence:</p><p>&middot; A PhD, or equivalent, in mathematics or a relevant branch of mathematics, physics, bioengineering or a closely related discipline.</p><p>&middot; Excellent communication and organisational skills.</p><p>&middot; The ability to work independently and as part of a multidisciplinary and multicultural team.</p><p>&middot; Ability to devise, advise on and manage a research programme.</p><p>&middot; A consistent track record of high-quality peer reviewed publications in cardiac electrophysiology modelling.</p><p>This full-time position (36.25 weekly hours) is available from 1st July 2026 [or as soon as possible thereafter] until 31st March 27. Many of our team have flexible working patterns so we&rsquo;re open to discuss flexible working arrangements with you.</p><p>If it sounds like you would be a good fit, we look forward to hearing from you.</p><p>For information about the School of Mathematical Sciences and active research themes see: http://www.nottingham.ac.uk/mathematics/index.aspx.</p><p>Informal enquiries may be addressed to Prof. Gary Mirams email: gary.mirams@nottingham.ac.uk. Please note that applications sent directly to this email address will not be accepted.</p><p>To find out more about the People and Culture in the School of Mathematical Sciences please visit our website: https://www.nottingham.ac.uk/mathematics/edi/edi.aspx</p>
            <p>
              Closing Date: 16 Jul 2026<br />
              Category: Research and Teaching (R&T)
            </p>
          ]]></description>
          <category><![CDATA[Research and Teaching (R&amp;T)]]></category>
          <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
        </item>
      
  </channel>
</rss>
