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Dr Timon S. Gutleb

Dr Timon S. Gutleb

Profile

I am a Lecturer in Scientific Computing at the University of Leeds.

Previously I was a PIMS-Simons postdoctoral fellow at the University of British Columbia from 2023-2024 and a postdoctoral research associate at the University of Oxford from 2022-2023 after having completed a PhD in applied mathematics at the Imperial College London in 2022 under the supervision of Sheehan Olver. As an undergraduate I studied physics (BSc, MSc), mathematics (MSc) and philosophy (BA, MA) at the University of Vienna from 2013 to 2018.

Research interests

My research focus is the development of computational algorithms and tools for natural science applications such as molecular quantum physics and collective behavior in biology, including specifically also machine learning models thereof. I am also interested in computational orthogonal polynomials and their applications in spectral methods as well as the aforementioned machine learning models.

<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://eps.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>

Qualifications

  • PhD in Mathematics
  • MSc in Mathematics
  • MSc & BSc in Physics
  • MA & BA in Philosophy
<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>
Projects
    <li><a href="//phd.leeds.ac.uk/project/2082-accurate-and-efficient-computation-of-special-functions">Accurate and efficient computation of special functions</a></li> <li><a href="//phd.leeds.ac.uk/project/2083-advances-in-the-machine-learning-of-many-body-interactions">Advances in the machine learning of many-body interactions</a></li> <li><a href="//phd.leeds.ac.uk/project/2084-efficient-numerical-methods-for-the-solution-of-fractional-differential-equations">Efficient numerical methods for the solution of fractional differential equations</a></li> <li><a href="//phd.leeds.ac.uk/project/2064-towards-real-time-digital-volume-correlation-for-imaging-applications">Towards real-time digital volume correlation for imaging applications</a></li>