Our Research

Our research is interdisciplinary and has impact across areas as diverse as social care, mathematics education, and animal welfare, with examples including:

• Catalyst Project - Improving community services for vulnerable people - A group of researchers from our school contributed to the "Identifying 'at risk' adults and children" initiative in this project.
• Machine learning for recognising tangled 3D objects - Funded by the Leverhulme Trust, this project will use machine learning to look at how we can teach computers to understand the 3D world, without using deep neural networks.
• Cow tracking - We're combining animal behaviour data, gathered using wireless tracking sensors, with mathematics, to help predict early signs of illness or other medical episodes in cows. By giving farmers an early indication of problems, we can improve cow health and welfare.
• Algorithmic fair division in dynamic, socially constrained environments - In this project we are developing a computer algorithm that will ensure fair division of indivisable assets between parties that have a claim on the asset (such as a valuable painting in a divorce case).
• Demand forecasting and dynamic pricing for e-grocery fulfilment - This Knowledge Transfer Partnership project, run with online delivery company Ocado, will improve delivery efficiency using Big Data, machine learning and forecasting.
• The Calabi problem for smooth Fano threefolds - This project studied the existence of natural notions of metrics on most three-dimensional positively curved shapes. Known as Fano varieties, these shapes are one of three kinds of building blocks of all other shapes and have a very rich geometry.
• Random-field effects in spin models: Supersymmetry, criticality, and universality - This project aims at clarifying the effects of random fields, one of the most common yet less understood types of disorder with many experimental analogues in physics, on a variety of spin models and unveiling their critical behaviour and universality principles.
• Stability of Brunn-Minkowski inequalities and Minkowski type problems for nonlinear capacity - This project is devoted to studying the stability of Brunn-Minkowski inequality for nonlinear capacity associated to A-harmonic PDEs for convex compact sets, as well as the related Minkowski problem.

Our work can have direct impact and help businesses thrive through Knowledge Transfer Partnerships. Through KTPs our researchers can evidence the value and impact of their work, while businesses benefit from expertise and cutting-edge research techniques.

Some of our KTPs have included:

• Professor Berthold Lausen was shortlisted in the 2022 KTP awards for his work with data consultancy Profusion.
• Working with the Port of Felixstowe to improve efficiency of complex scheduling processes. We assisted in the development of optimisation algorithms using artificial intelligence, which helped with both scheduling staff resources and solving scheduling problems. This reduced waste and improved customer service.
• Carrying out a data science KTP with knowledge resource company Mondaq that helped them make the most of large data sets. They were awarded Winner of Best KTP Partnership 2018.
• Members of our data science group are currently working on a KTP project with online grocery company Ocado, that will utilise Big Data with machine learning and forecasting to improve delivery efficiency, which will reduce cost to the company and the carbon footprint of deliveries.

Our academics also act as supervisors for postgraduate research degrees in their specialist areas, and co-supervise research students working on interdisciplinary projects with colleagues across the University. PhD students in the School join one of our research themes and become part of a vibrant, collaborative research community during their time with us.

We are always interested in welcoming new postdoctoral researchers and PhD students through external competitive funding. If you are interested in applying for one of the opportunities below at Essex, you can contact a researcher working in your area of interest or get in touch with the relevant Research Theme Leads. Details of our current research themes can be found under our mathematics and data science research groups.

For postdoctoral researchers, the following schemes may be relevant:

• EPSRC postdoctoral fellowships - Supporting outstanding early-career researchers in engineering and the physical sciences. No deadline.
• Newton International Fellowship - Two-year fellowships for researchers currently based overseas who do not hold UK citizenship. The deadline is in mid-March, and you should ideally contact a potential mentor at least two or three months in advance.
• Marie Curie fellowships - Typically with deadlines in September. Please contact us at least 6 to 8 months in advance to ensure proper support.
• Royal Society University Research Fellowships - Prestigious 5–8 year awards. The deadline is in mid-September, and you should ideally contact a potential mentor at least two or three months in advance.
• Royal Society Dorothy Hodgkin Fellowships - For scientists who require a flexible working pattern due to personal circumstances, such as caring responsibilities or health conditions. The deadline is in early September, and you should ideally contact a potential mentor at least two or three months in advance.
• Leverhulme Trust Research Leadership Awards - Supporting researchers ready to build a research team of their own.
• Newton Advanced Fellowships - For 2-3 years visits to the UK from overseas.
• The Royal Commission for the Exhibition of 1851 Fellowships - Three-year research scholarships with a deadline in October.

If you are considering applying for any of these opportunities, early contact is essential so that we can provide advice and institutional support for your application.

Academics in our school have published in a range of journals related to their specialist areas within mathematics and data science including:

• European Journal of Operational Research
• Ecology
• Biostatistics
• Statistics in Medicine
• Statistics and Computing
• Bernoulli
• Journal of Applied Probability
• Physica A: Statistical Mechanics and its Applications
• Frontiers in Computational Neuroscience
• Chaos, Solitons and Fractals
• Physical review E.
• Advances in Mathematics
• Journal of Algebra
• Transactions of the American Mathematical Society
• Journal of Physics A: Mathematical and Theoretical
• Journal of Mathematical Physics
• International Mathematics Research Notices
• Memoirs of the American Mathematical Society
• Math Zeitschrift
• Journal of Pure and Applied Algebra

We have organised and taken part in a range of conferences and workshops focusing on aspects of mathematics and data science including:

• AGGITatE 2025, an international conference exploring advances in group theory and representation theory.
• Data Science Week 2025, led by the Institute of Analytics and Data Science to showcase the potential of data science and artificial intelligence.
• PDEs at Essex 2025, the 2025 workshop was held in June and examined "Regularity Theory of PDEs and Calculus of Variations".
• PDEs at Essex 2024, a three day workshop held in February with a focus on the theme "Problems in potential theory of nonlinear elliptic PDEs".