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      <p style="margin-bottom:0cm"><span style="font-family:"Times New Roman",serif;color:black">We are
          recruiting for the Autumn 2025 cohort for the Centre for
          Doctoral Training in Mathematics for Our Future Climate! We
          have an open PhD position at the intersection of data
          assimilation and machine learning at the University of
          Reading.</span><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><span style="font-family:"Times New Roman",serif;color:black">The
          positions are for fully funded 4-year PhD studentship.
          Interested students should apply as soon as possible through
          the University of Reading's application page at </span><u><span style="font-family:"Times New Roman",serif;color:#3465A4"><a href="https://www.reading.ac.uk/maths-and-stats/phd/mathematics-for-our-future-climate" class="moz-txt-link-freetext">https://www.reading.ac.uk/maths-and-stats/phd/mathematics-for-our-future-climate</a></span></u><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><span style="font-family:"Times New Roman",serif;color:black">Feel
          free to contact me (</span><u><span style="font-family:"Times New Roman",serif;color:#3465A4"><a href="mailto:e.bach@reading.ac.uk" class="moz-txt-link-freetext">e.bach@reading.ac.uk</a></span></u><span style="font-family:"Times New Roman",serif;color:black">) with
          any questions!</span><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><b><span style="font-family:"Times New Roman",serif;color:black">Project
            description</span></b><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><i><span style="font-family:"Times New Roman",serif;color:black">Machine
            Learning Approaches in Bayesian and Ensemble Data
            Assimilation</span></i><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><span style="font-family:"Times New Roman",serif;color:black">Probabilistic
          data assimilation (DA) is the process of combining models with
          observations to obtain the filtering distribution—the
          conditional probability over states given past and present
          observations. Due to computational limitations, typically only
          rough approximations of the true filter are tractable. This
          project proposes to use machine learning (ML) to learn new DA
          algorithms that better approximate the true filter, holding
          the potential to improve forecasts and quantify their
          uncertainty. This will be done using strictly proper scoring
          rules, skill metrics with appealing theoretical properties for
          this purpose.<br>
          <br>
          This project will focus on learning ensemble DA algorithms for
          use in high-dimensional chaotic systems such as the
          atmosphere. Initial application will be to idealised problems,
          but scaling up these methods to operational weather prediction
          will also be explored. Theoretical issues about learnability
          and comparisons to other methods will also be considered.<br>
          <br>
          The combination of ML with DA is an active and quickly
          expanding area of research. However, the learning DA
          algorithms is an underexplored field and has the potential to
          significantly improve on current DA methods used for weather
          and climate forecasting. The student would thus be at the
          frontier of high-impact DA research, working with
          world-leading institutions on research in DA (Reading), Earth
          observation (NCEO), and ML (Turing Institute).<br>
        </span><span style="color:black"></span></p>
      <p style="margin-bottom:0cm"><b><span style="font-family:"Times New Roman",serif;color:black">About
            the MFC CDT</span></b><span style="color:black"></span></p>
      <p><span style="font-family:"Times New Roman",serif;color:black">Are
          you passionate about using mathematics to tackle the pressing
          challenges of climate change? The EPSRC Centre for Doctoral
          Training in the Mathematics for our Future Climate (MFC CDT)
          invites you to apply for our exciting PhD programme. A dynamic
          and interdisciplinary PhD programme that harnesses the power
          of mathematics to address the urgent issues presented by
          climate change. Jointly run by Imperial College London, the
          University of Reading, and the University of Southampton, and
          a range of partners across business, industry, charities, and
          government.</span><span style="color:black"></span></p>
      <p><span style="font-family:"Times New Roman",serif;color:black">The
          MFC CDT will train highly skilled mathematicians to become
          future leaders in innovative research, developing
          environmental prediction technologies, interpreting very large
          datasets relating to the Earth system, and modelling the risk
          associated with extreme weather and climate change.</span><span style="color:black"></span></p>
      <p><b><span style="font-family:"Times New Roman",serif;color:black">Why
            Choose the MFC CDT PhD Programme?</span></b><span style="color:black"></span></p>
      <ul type="disc">
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Innovative
              Research Opportunities:</span></b><span style="font-family:"Times New Roman",serif"> Engage
            in research focused on weather and climate modelling, data
            analysis, and novel mathematical approaches to environmental
            challenges.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Interdisciplinary
              Collaboration:</span></b><span style="font-family:"Times New Roman",serif"> Work
            with experts from diverse fields, including climate science,
            atmospheric physics, and related disciplines.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Cohort
              Culture:</span></b><span style="font-family:"Times New Roman",serif"> Be
            part of a vibrant cohort-based research environment and
            enhance your personal skills through a bespoke training
            programme.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Tailored
              Internships:</span></b><span style="font-family:"Times New Roman",serif"> Gain
            practical experience with external partners in key sectors
            such as insurance, energy, water, and marine industries.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">State-of-the-Art
              Facilities:</span></b><span style="font-family:"Times New Roman",serif"> Access
            cutting-edge facilities and resources to support your
            research endeavours.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Mentorship
              from Renowned Faculty:</span></b><span style="font-family:"Times New Roman",serif"> Benefit
            from guidance by experienced faculty members dedicated to
            your academic and professional growth.</span></li>
        <li style="color:black;mso-list:l0 level1 lfo1"><b><span style="font-family:"Times New Roman",serif">Fully
              Funded Studentships:</span></b><span style="font-family:"Times New Roman",serif"> Receive
            a stipend, including a London weighting, PhD fees for 4
            years, and a generous allowance for research-related
            activities.</span></li>
      </ul>
      <p><b><span style="font-family:"Times New Roman",serif;color:black">Join
            Us in Shaping the Future</span></b><span style="color:black"></span></p>
      <p><span style="font-family:"Times New Roman",serif;color:black">Your
          expertise and passion for mathematics can play a pivotal role
          in advancing our understanding of climate change. Applications
          are now open to become part of a community dedicated to making
          a positive impact on the world. For more information and to
          apply, visit </span> <span style="color:black"><a href="https://mfccdt.ac.uk/"><span style="font-family:"Times New Roman",serif;color:#3465A4">https://mfccdt.ac.uk/</span></a></span><span style="font-family:"Times New Roman",serif;color:black"> or
          contact the Admissions team on </span><span style="color:black"><a href="mailto:Admission.CDT-MFC@reading.ac.uk"><span style="font-family:"Times New Roman",serif;color:#3465A4">Admission.CDT-MFC@reading.ac.uk</span></a></span><span style="font-family:"Times New Roman",serif;color:black"> </span><span style="color:black"></span></p>
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