About me
I am an Assistant Professor in the Computational Science group within the Centre for Analysis, Scientific Computing and Applications at TU Eindhoven. My research interests include large scale numerical linear algebra (theory and applications), data assimilation, and treatment of covariance matrices. Alongside my research I’m interested in outreach and scientific crafting. Contact me at j[.]m[.]tabeart[at]tue[.]nl and find out more about the Computational Science group here.
Open positions
Together with Wouter Huberts from Biomedical Engineering, I was awarded funding from Eindhoven Artificial Intelligence Institute the project Hy-Credibility. The first round of recruitment is currently ongoing.
As part of the funded Perspectif grant Digital Dikes Michiel Hochstenbach and are recruiting a postdoc on Data-driven and reduced-order models for dike monitoring and safety. Vacancy to appear on the TU Eindhoven website.
I also have openings to supervise Bachelor and Master Final Projects – some of the topics I am offering can be found here.
News
I’ve been appointed to the Eindhoven Young Academy of Engineering for the period September 2026 - 2030.
Our paper with collaborators in Edinburgh and CERFACS has been accepted at IMA Journal of Numerical Analysis. We approximate block alpha-circulant preconditioners for all-at-once diffusion-based covariance operators for problems coming from ocean data assimilation on arXiV. For some non-technical insight into this project, I wrote a blog post for the DARC blog about how computational constraints can lead us to really interesting mathematical challenges.
Registration for Dutch Mastermath courses is now open. I’m teaching a course on Advanced Numerical Linear Algebra with Applications (to Machine Learning and Data Assimilation) with Victorita Dolean-Maini. Find out more and enrol here. The first half of the lecture notes for the course are available on arXiv.
Interested in better understanding the role of numerical linear algebra in data assimilation? Together with collaborators from the PVDAP network we have written an introductory paper aimed at those new to data assimilation on arXiv, to appear in SIAM Review.
Work and education history
Find my CV here October 2023 - Present: Assistant Professor at TU Eindhoven. University teaching qualification awarded September 2025.
October 2022 - October 2023: Fulford Non-Stipediary Fellow at Somerville College
September 2022 - October 2023: Hooke Fellow in the Mathematical Institute at the University of Oxford in the Numerical Analysis group.
2019 - August 2022: PDRA in the School of Mathematics at The University of Edinburgh working with Dr John W. Pearson
Spring 2020: Semester Postdoctoral Fellow at the Institute for Computational and Experimental Research in Mathematics at Brown University
2016 - 2019: PhD at the University of Reading with Professor Sarah Dance, Dr Amos Lawless, Professor Nancy Nichols and Dr Joanne Waller. Read my thesis here
2015 - 2016: MRes at Imperial College, London and University of Reading as part of the Mathematics of Planet Earth Centre for Doctoral Training
2011 - 2015: MMath at the University of Bath with Study Year Abroad at Université Joseph Fourier (now Université Grenoble Alpes)
Some recent papers
An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
Ieva Daužickaitė, Melina A. Freitag, Selime Gürol, Amos S. Lawless, Alison Ramage, Jennifer A. Scott, Jemima M. Tabeart
Block Alpha-Circulant Preconditioners for All-at-Once Diffusion-Based Covariance Operators
Jemima M. Tabeart, Selime Gürol, John W. Pearson, Anthony T. Weaver
Saddle point preconditioners for weak-constraint 4D-Var
Jemima M. Tabeart and John W. Pearson
Stein-based preconditioners for weak-constraint 4D-var
Davide Palitta and Jemima M. Tabeart
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference
Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer and Akil Narayan
Saddle point preconditioners for weak-constraint 4D-Var
Jemima M Tabeart and John W Pearson
The conditioning of least squares problems in preconditioned variational data assimilation
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Nancy K Nichols, Joanne A Waller
The impact of using reconditioned correlated observation‐error covariance matrices in the Met Office 1D‐Var system
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Stefano Migliorini, Nancy K Nichols, Fiona Smith, Joanne A Waller
Improving the condition number of estimated covariance matrices
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Nancy K Nichols, Joanne A Waller
The conditioning of least‐squares problems in variational data assimilation
Jemima M Tabeart, Sarah L Dance, Stephen A Haben, Amos S Lawless, Nancy K Nichols, Joanne A Waller
Supervision
Hisham Elzayyadi (October 2024 – present) PhD student
Teaching
2026–27
2BMC30 – Numerical Linear Algebra (responsible lecturer)
MasterMath – Advanced numerical linear algebra with applications (co-lecturer)
JBM180 – Linear algebra for data analysis (responsible lecturer/instructor)
2025–26
2WBB0 – Calculus for computer scientists (lecturer)
2DD40 – Math 1 (instructor)
2DME20/2MMD10 – Nonlinear Optimization (instructor)
JBM180 – Linear algebra for data analysis (responsible lecturer)
MasterMath – Advanced numerical linear algebra with applications (co-lecturer)
2024–25
2DD40 – Math 1 (instructor)
2DRR00 – Linear algebra and Applications (responsible lecturer and instructor)
2DBA0 – Matrices and differential equations (instructor)
Other activities
I’m trying to fly less for work and personal travel, and I’m always happy to share ideas and route planning advice. I blog about my exploits via active travel and public transport at Adventures of a Mathematician. Some recent non-flight journeys include: Eindhoven - Toulouse - Edinburgh - Eindhoven Eindhoven to: Copenhagen, Vienna, Chemnitz, Geneva, Glasgow, Oxford