About the role

The University of Leicester is seeking an ambitious and creative researcher to join the School of Computing and Mathematical Sciences as a Research Associate in the Mathematics of Planet Earth. This post is funded through the Horizon Europe project Ocean Nexus: Assessing consequences in the cascading of climate tipping in the ocean–marine ecology–society connection, a major four-year international collaboration involving leading UK and European universities and research centres. The University of Leicester leads the largest work package within the project, focused on cascading effects and tipping in marine ecosystems.

You will undertake research centred on the development and analysis of mathematical and computational tools to investigate tipping points in marine ecological systems and to forecast future ecosystem states under extreme climate variability. The role involves building and analysing process-based and data-driven models, performing large-scale numerical simulations, and working with complex spatiotemporal datasets to identify early warning signals of critical transitions. The post holder will be embedded within a highly active applied mathematics research environment and will collaborate closely with academic partners in the UK and overseas, contribute to publications and reports, present findings at international conferences, and support the wider research activity of the group.

About you

You will have completed, or be close to completing, a PhD in mathematics, physics, or a closely related discipline, with a strong background in applied or theoretical dynamical systems, mathematical modelling in the life sciences, and the analysis of complex systems. You will be able to demonstrate research experience through high-quality publications, alongside excellent written and verbal communication skills, and the ability to present research outcomes to academic audiences.

You will have expertise in at least one of applied dynamical systems, numerical modelling, or data-driven methods such as machine learning and advanced time series analysis, and will be comfortable working with large datasets and developing research software in MATLAB and or Python. You will be motivated to work both independently and collaboratively within an interdisciplinary and international research setting, with the capacity to contribute to mentoring students and early career researchers and to engage fully with the research culture of the School of Computing and Mathematical Sciences at the University of Leicester.

Additional information

For informal enquiries, please contact Dr Andrew Morozov on [email protected]

We anticipate that interviews will take place on June 16th, 17th or 19th.

As part of the University’s ongoing commitment to professional development, this role will also be considered on a seconded basis for existing staff members. Please ensure this is discussed with your line manager prior to applying. More information regarding secondments can be found here.

The University of Leicester has been changing the world, and changing people’s lives, for 100 years. When you join us, you’ll become part of a community of Citizens of Change, which includes not only our staff and our current students but also thousands of Leicester graduates around the world.

As a diverse and forward-thinking employer, we embed the principles of equity, diversity and inclusion into everything we do. That includes not just our core missions of teaching and research, but also our support for staff, students and our local community through our values of Inspiring, Impactful and Inclusive through our values of Inspiring, Impactful and Inclusive.

We’re committed to the wellbeing of all our staff and to the sustainability of our environment, on our campus and beyond. We offer a competitive salary package, excellent pension scheme and a generous annual leave allowance, along with opportunities to develop your career in a supportive and collaborative environment.

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Research Associate in Mathematics of Planet Earth

About the role

About you

Additional information

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