Senior Research Associate 'statistical > Methods

2 weeks ago


Lancaster, United Kingdom Lancaster University Full time

Postdoctoral research opportunity in statistical methods for adaptive surveillance for controlling and eradicating endemic livestock diseases.

Are you excited by using data science in disease control? If you are, then we are looking for a skilled and motivated individual to join our team developing Monte Carlo based approaches to Bayesian inference to inform disease surveillance for control and eradication of infectious diseases in data-poor scenarios. This project is funded by BBSRC as part of an international collaboration to tackle “end-game” scenarios in eradicating infectious diseases with a focus on livestock in Kenya and Turkey.

The successful applicant must have a strong interest and track record to PhD level in Bayesian inference and computationally intensive statistical methods such as Markov-chain Monte Carlo and Approximate Bayesian Computation applied to epidemiological data. They must have a high level of proficiency in a data-orientated scripting language such as R or Python, and be committed to developing high quality software implementations of their methods using modern software development techniques such as functional programming (e.g. TensorFlow, PyTorch), packaging systems (e.g. CRAN, PyPI), and Git version control.

Desirable (though not essential) skills are familiarity with epidemic modelling, Gaussian processes, and accelerated computational hardware (GPU, manycores, etc).

Lancaster is one of the UK’s top departments in Mathematics and Statistics, ranked 7th equal in the 2021 Research Excellence Framework, and 1st for the impact of its research.

The Department, which holds an Athena SWAN Bronze Award and strives to provide a supportive and welcoming environment for early career researchers.

Lancaster University is fully committed to flexible working, and applicants who wish to work remotely are welcome to apply.



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