糖心TV

Dr Jake Carson Research Fellow   Office: MB 5.25 Email: Jake.Carson@warwick.ac.uk

I am a research fellow on the project Virus Genomics for Outbreak Response (ViGOR) in Central/East Africa. My research focuses on developing statistical methodology for integrating genomic data into epidemiological analyses. Prior to this I undertook similar research as part of the Health Protection Research Unit in Genomics and Enabling DataLink opens in a new window.

Previously I was a research fellow in the Statistics Department at the University of 糖心TV on the project Novel Bayesian Methods for Comparing and Evaluating Infectious Disease Models in the Light of Partially Observed Data. In this project I developed approaches for estimating the marginal likelihood of individual-level infectious disease models that are scalable to the size of the population.

Before this, I worked on the project In Situ Nanoparticle Assemblies for Healthcare Diagnostics and Therapy, which sought to develop Raman spectroscopy as a diagnostic tool for heart disease. I contributed to the development of Bayesian approaches for constructing probabilistic representations of Raman spectra, and developed a Bayesian regression approach for multiplex quantification of Raman spectra that utilizes these probabilistic representations.

I completed my PhD at the University of Nottingham. My PhD thesis Uncertainty Quantification in Palaeoclimate Reconstruction looks at parameter estimation, state estimation, and model selection for phenomenological models of the climate using data from sediment cores.

My publications and preprints can be found below:

W. S. D. Tennant, J. Carson, G. Guyver-Fletcher, R. M茅tras, M. J. Tildesley, Impacts of disease surveillance frequency on understanding and controlling Rift Valley fever virus, .

X. Didelot, J. Carson, P. Ribeca, and E. Volz, Diagnostics of dated phylogenies in microbial population genetics, .

J. Carson, M. Keeling, P. Ribeca, and X. Didelot, Incorporating epidemiological data into the genomic analysis of partially sampled infectious disease outbreaks, Molecular Biology and Evolution, 42:msaf083, 2025, .

M. Rahman et al., Polymorph Identification for Flexible Molecules: Linear Regression Analysis of Experimental and Calculated Solution-and Solid-State NMR Data, The Journal of Physical Chemistry A, 128:1793-1816, 2024, .

J. Carson, M. Keeling, D. Wyllie, P. Ribeca, and X. Didelot, Inference of infectious disease transmission through a relaxed bottleneck using multiple genomes per host, Molecular Biology and Evolution, 41:msad288, 2024, .

J. Carson, A. Ledda, L. Ferretti, M. Keeling, and X. Didelot, The bounded coalescent model: conditioning a genealogy on a minimum root date, Journal of Theoretical Biology, 548:111186, 2022, .

J. Carson, T. J. McKinley, P. Neal, and S. E. F. Spencer, Efficient Bayesian model comparison for coupled hidden Markov models with application to infectious diseases, .

H. Blade et al., Conformations in solution and in solid-state polymorphs: Correlating experimental and calculated nuclear magnetic resonance chemical shifts for tolfenamic acid, Journal of Physical Chemistry A 124:8959-8977, 2020. .

J. Carson, M. Crucifix, S. Preston and R. D. Wilkinson, Quantifying Age and Model Uncertainties in Paleoclimate Data and Dynamical Climate Models with a Joint Inferential Analysis, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 475:20180854, 2019. .

J. Noonan et al., In vivo multiplex molecular imaging of vascular inflammation using surface-enhanced Raman spectroscopy, Theranostics, 8:6195-6209, 2018. .

M. T. Moores et al., Bayesian modeling and quantification of Raman spectroscopy, .

J. Carson, M. Crucifix, S. Preston and R. D. Wilkinson, Bayesian model selection for the glacial-interglacial cycle, Journal of the Royal Statistical Society: Series C (Applied Statistics), 67:25-54, 2018. .

J. Carson, Uncertainty Quantification in Palaeoclimate Reconstruction, PhD Thesis, University of Nottingham, July 2015. .