PhD Studentship: Modelling of Human Population Registers

Project Title: Modelling of Human Population Registers

Fully funded studentship

Supervisors: The student will be supervised by an interdisciplinary team across four institutions

(1) Statistics (Dr Bruno Santos) and Statistical Ecology (Dr Eleni Matechou), University of Kent, 

(2) Demography (Dr Eleonora Mussino), University of Stockholm, 

(3) Bayesian Inference/Statistical Ecology (Professor Ruth King), University of Edinburgh,

(4) Ecology/Statistical Ecology (Dr Blanca Sarzo), University of Valencia.

Funding: The project has been awarded funding by the University of Kent Migration and Movement Signature Research Theme, a vibrant community of over 100 scholars, and research students. Funding is available for 3 years, for home and international students.

Home and International candidates are eligible to apply. Scholars will receive the following:

Annual stipend at UKRI rates (£17,668 in 2022/23); Annual tuition fees at Home rates (£4,596 in 2022/23)

Project aims: The project aims to provide a general and unifying modelling framework for estimating population size from human population registers. The student will bring together multiple systems estimation (MSE)([1], [2]), and capture-recapture (CR) ([3], [4], [5]) modelling approaches to develop sophisticated models for high-dimensional, long time-series data. They will also implement, extend and develop corresponding Bayesian algorithms for fitting the models to real data from several countries such Sweden and Norway and they will extend and adapt the models for corresponding large ecological data.

The new models to be developed by the student will overcome the shortcomings of existing approaches, and will be applicable to high-dimensional data sets typically observed in human populations, and increasingly in wildlife populations.

For more details on the project and the Migration and Movement SRT please see: https://blogs.kent.ac.uk/seak/2022/11/22/migration-and-movement-srt-project/

Person specification: We seek a candidate with a strong quantitative background, eg. an MSc in Statistics or with high statistics content, or a background in demographic modelling. Experience coding in R, or similar, is essential.

Research excellence: The student will join the thriving Statistical Ecology @ Kent research group, and the Migration and Movement Signature Research Theme, being supervised by leading researchers in demography, statistics and statistical ecology. They will also be members of the UK-wide National Centre for Statistical Ecology. They will attend London Taught Course Centre training, NCSE seminars, and SE@K specialist training and they will present research results at a range of appropriate national and international conferences. There will be ample opportunity for independent development, with the student gaining transferable knowledge of modern data science and statistics.

Please email Dr Eleni Matechou (e.matechou@kent.ac.uk) if you are interested in applying for the project or have any questions about the project or the application process.

References 

[1] King, R., et al (2014). Estimating prevalence of injecting drug users and associated heroin‐related death rates in England by using regional data and incorporating prior information. JRSS A, 177(1), 209-236. 

[2] Zhang, S. X., & Larsen, J. J. (2021). Estimating the size of the human trafficking problem: MSE and other strategies. Crime & Delinquency, 67(13-14),

[3] McCrea, R. S., & Morgan, B. J. (2014). Analysis of capture-recapture data. CRC Press. 

[4] Matechou, E., & Argiento, R. (2022). Capture-recapture models with heterogeneous temporary emigration. JASA, https://www.tandfonline.com/doi/full/10.1080/01621459.2022.2123332

[5] King, R., et al Large Data and (Not Even Very) Complex Ecological Models: When Worlds Collide. arXiv preprint arXiv:2205.07261.

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