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Dr Jere Koskela

As of 1 August 2023 I will start as reader at the Newcastle University School of Mathematics, Statistics, and Physics. This page will not be maintained beyond that date.

I'm an associate professor at the statistics department at Warwick. My research interests include Monte Carlo methods, statistical inference from stochastic processes and in settings with intractable likelihood, Bayesian nonparametric statistics, coalescent processes, and mathematical population genetics.

I'm also one of the organisers of the Warwick Statistics Internship Scheme. Illustrative project descriptions for undergraduate summer internships are available on the scheme website.


I'm teaching ST341/418 Statistical Genetics in 2022/23.


  • P A Hanson, P A Jenkins, J Koskela, and D Spanò. Diffusion limits at small times for coalescent processes with mutation and selection. [arXiv]
  • A Ignatieva, M Favero, J Koskela, J Sant, and S R Myers. The distribution of branch duration and detection of inversions in ancestral recombination graphs. [bioRxiv]
  • J Koskela, K Łatuszyński, and D Spanò. Bernoulli factories and duality in Wright-Fisher and Allen-Cahn models of population genetics. [arXiv]

Peer reviewed publications

  • S Brown, P A Jenkins, A M Johansen, and J Koskela. Weak convergence of non-neutral genealogies to Kingman's coalescent. Stochastic Processes and their Applications 162:76-105, 2023. [SPA] [arXiv] [WRAP]
  • E Árnason, J Koskela, K Halldórsdóttir, and B Eldon. Sweepstakes reproduction via pervasive and recurrent selective sweeps. eLife 12:e80781, 2023. [eLife] [bioRxiv] [WRAP] [Dryad] [GitHub]
  • J Sant, P A Jenkins, J Koskela, and D Spanò. EWF: Simulating exact paths of the Wright-Fisher diffusion. Bioinformatics 39(1):btad017, 2023. [Bioinformatics] [arXiv] [WRAP]
  • F Baumdicker, G Bisschop, D Goldstein et al. (there are 32 of us). Efficient ancestry and mutation simulation with msprime 1.0. Genetics 220(3):iyab229, 2022. [Genetics] [bioRxiv] [WRAP]
  • J Koskela. Zig-zag sampling for discrete structures and non-reversible phylogenetic MCMC. Journal of Computational and Graphical Statistics 31(3):684-694, 2022. [JCGS] [arXiv] [WRAP] [GitHub]
  • A Mahmoudi, J Koskela, J Kelleher, Y Chan, and D Balding. Bayesian inference of ancestral recombination graphs. PLOS Computational Biology 18(3):e1009960, 2022. [PLOSCG] [WRAP] [GitHub]
  • J Sant, P A Jenkins, J Koskela, and D Spanò. Convergence of likelihood ratios and estimators for selection in non-neutral Wright-Fisher diffusions. Scandinavian Journal of Statistics 49(4):1728-1760, 2022. [SJS] [arXiv] [WRAP]
  • S Brown, P A Jenkins, A M Johansen, and J Koskela. Simple conditions for convergence of sequential Monte Carlo genealogies with applications. Electronic Journal of Probability 26, Paper 1, 2021. [EJP] [arXiv] [WRAP]
  • J Blath, E Buzzoni, J Koskela, and M Wilke Berenguer. Statistical tools for seed bank detection. Theoretical Population Biology 132:1-15, 2020 [TPB] [arXiv] [WRAP] [GitHub]
  • J Koskela, P A Jenkins, A M Johansen, and D Spanò. Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo. Annals of Statistics 48(1):560-583, 2020 [AoS] [arXiv] [WRAP]
  • J Koskela, D Spanò, and P A Jenkins. Consistency of Bayesian nonparametric inference for discretely observed jump diffusions. Bernoulli 25(3):2183-2205, 2019 [Bernoulli] [arXiv] [WRAP]
  • J Koskela and M Wilke Berenguer. Robust model selection between population growth and multiple merger coalescents. Mathematical Biosciences 311:1-12, 2019 [MB] [arXiv] [WRAP] [GitHub]
  • J Koskela. Multi-locus data distinguishes between population growth and multiple merger coalescents. Statistical Applications in Genetics and Molecular Biology 17(3):20170011, 2018 [SAGMB] [arXiv] [WRAP] [GitHub]
  • J Koskela, P A Jenkins, and D Spanò. Bayesian nonparametric inference for Λ-coalescents: posterior consistency and a parametric method. Bernoulli 24(3):2122-2153, 2018 [Bernoulli] [arXiv] [WRAP]
  • J Koskela, D Spanò, and P A Jenkins. Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo. Statistics and Computing 28(1):131-144, 2018 [S&C] [arXiv] [WRAP]
  • J Koskela, P A Jenkins, and D Spanò. Computational inference beyond Kingman's coalescent. Journal of Applied Probability 52(2):519-537, 2015 [JAP] [arXiv] [WRAP]

Other published work

  • J Koskela. Genealogical processes of non-neutral populations. Bernoulli News 29(2):11-14, 2022. [Link]
  • J Koskela and A Q Wang. Discussion contribution on "Quasi-stationary Monte Carlo and the ScaLE algorithm" by M Pollock, P Fearnhead, A M Johansen, and G O Roberts, published in the Journal of the Royal Statistical Society Series B 58(5):1167-1221, 2020 [JRSSB]


  • PI, EPSRC research grant EP/V049208/1, Mathematical foundations of non-reversible MCMC for genome-scale inference (£80k), 2021-2022.
  • PI, EPSRC New Investigator Award EP/R044732/1, Exact scalable inference for coalescent processes (£100k), 2018-2020.
  • Co-PI, DFG SPP1819 start-up grant, Population genomics of highly fecund codfish (16k€). Joint with Bjarki Eldon (PI) and Maite Wilke Berenguer (Co-PI), 2017-2018.

Other grant involvement

  • Collaborator, Icelandic Centre for Research Grant of Excellence 185151-051, Population genomics of highly fecund codfish. PIs: Einar Arnason (corresponding PI, University of Iceland), Katrin Halldorsdottir (University of Iceland), Alison Etheridge (University of Oxford), Wolfgang Stephan (Berlin Natural History Museum), Bjarki Eldon (Berlin Natural History Museum).

Workshops and organisation

Biographical sketch

  • 2021-Present: Associate professor at the Department of Statistics, University of Warwick.
  • 2017-2021: Assistant professor at the Department of Statistics, University of Warwick.
  • 2016-2017: Postdoc with Jochen Blath at TU Berlin.
  • 2013-2016: PhD with Dario Spanò and Paul Jenkins at MASDOC, University of Warwick. My thesis is available here.
  • 2012-2013: MSc at MASDOC, University of Warwick.
  • 2008-2012: MMORSE at the Department of Statistics, University of Warwick.

Research students

I'm currently supervising the following:

My former students include:

Prospective students: feel free to get in touch. See here for some illustrative ideas of directions for projects.

mugshot of me


Dr Jere Koskela
Department of Statistics
University of Warwick
Coventry, CV4 7AL
United Kingdom


+44(0)24 7652 8068


j dot koskela at warwick dot ac dot uk