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    <title>Jobs at Lancaster University | School of Mathematical Sciences</title>
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          <title><![CDATA[Senior Research Associate – MARS / IceDice (0540-26)]]></title>
          <link>https://hr-jobs.lancs.ac.uk/rss/click.aspx?ref=0540-26</link>
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          <description><![CDATA[
            <p id="isPasted"><strong>Senior Research Associate &ndash; MARS / IceDice</strong></p><p>The School of Mathematical Sciences at Lancaster University is seeking to appoint a Senior Research Associate (SRA) to work within &lsquo;<a href="https://www.lancaster.ac.uk/mathematics-for-ai-in-real-world-systems/">MARS: Mathematics for AI in Real-world Systems</a>&rsquo;, contributing to the NERC-funded project &lsquo;IceDice: Predicting the stochastic behaviour of West Antarctica&rsquo;s Marine Ice Sheet&rsquo;.&nbsp;</p><p><strong>About the role</strong></p><p>The IceDice project aims to provide reliable probabilistic forecasts of the West Antarctic Ice Sheet&rsquo;s contribution to future sea level rise &ndash; information of enormous societal and economic value for coastal planning and climate adaptation worldwide.&nbsp;</p><p>Your research will develop and apply novel Bayesian machine learning methods &ndash; in particular physics-informed Gaussian processes and/or neural operators&ndash; to build accurate probability density functions (PDFs) of future Antarctic sea level contributions. &nbsp;</p><p>Working as part of a collaborative team spanning British Antarctic Survey and the University of Cambridge, you will be based at Lancaster and work with Dr Henry Moss to:</p><ul><li>Develop machine learning emulators for the WAVI ice-sheet model to serve as efficient surrogates for large-scale Bayesian inference.</li><li>Develop utility-function-based experimental design methods to identify the computer simulations and observational surveys that maximise information about future sea level for a given computational cost.</li><li>Work closely with ice-sheet modellers at the British Antarctic Survey to apply probabilistic methods to realistic West Antarctic domains.</li><li>Publish high-quality research in leading peer-reviewed journals and present at national and international conferences.&nbsp;</li></ul><p><strong>What we&rsquo;re looking for</strong></p><ul><li>PhD in statistics, machine learning, physics or a closely related discipline.</li><li>Research experience in Bayesian methods, probabilistic modelling, or scientific machine learning.&nbsp;</li><li>Experience with Gaussian processes, MCMC methods, or uncertainty quantification for expensive computational simulators.</li><li>An interest in applying mathematical methods to real-world environmental challenges, and willingness to collaborate across disciplinary boundaries.</li><li>Experience with Python, or equivalent scientific computing languages.&nbsp;</li></ul><p>The IceDice project connects you to a world-leading collaborative team at the British Antarctic Survey and the University of Cambridge, with opportunities to engage with high-profile climate science and policy impact.</p><p>Candidates who are considering making an application are strongly encouraged to contact Dr Henry Moss (h.moss@lancaster.ac.uk) to discuss the role.</p><p>This is a full-time, fixed-term position for 22 months or until 31/08/2028 (whichever comes first). Flexible working arrangements will be considered, but you will be expected to be present on the Lancaster campus a minimum of two days per week.</p>
            <p>
              Closing Date: 26 Jul 2026<br />
            </p>
            <p>
              Department: Research
            </p>
            <p>Salary: &#163;39,906 to &#163;46,049 (Full time, indefinite with end date)</p>
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          <category><![CDATA[Research]]></category>
          <pubDate>Sun, 28 Jun 2026 00:00:00 GMT</pubDate>
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