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Postdoc Research Associate, Department of Geography - Cambridge, UK

Postdoc Research Associate, Department of Geography - Cambridge, UK

Cambridge, United Kingdom
Category
Logistics
Closing Date for Receipt of Applications: 24th January 2022
Interview date: 7th February 2022
Anticipated Start Date: 1st April 2022 or as soon as possible thereafter, for a 14-month appointment.
Salary range: £33,309 - £40,927

Applications are invited for a Research Associate position for a fixed-term of 14 months to work on a new project funded by the Isaac Newton Trust at the Department of Geography, University of Cambridge (http://www.geog.cam.ac.uk). For further details, please contact Dr Francesco Muschitiello, fm476@cam.ac.uk (tel: 01223 333193).
Description
Improving probabilistic models for automated alignment of Palaeoclimate records.

The stratigraphic correlation of marine sediment cores, speleothems and ice core records, plays a central role in palaeoclimate research as it is used to develop mutually consistent timescales for climate proxies measured in these archives.

To present, the vast majority of stratigraphic correlations are performed manually. However, this approach is inherently subjective, often difficult to reproduce and comes without quantification of the confidence of correlations. Altogether, this prevents researchers to examine the robustness of their conclusions, including the statistical evaluation of rates of change and lead-lag relationships between events observed in different palaeoclimate archives. Alignment algorithms grounded on probability theory can help us address these limitations. I
n particular, they have an enormous and, as of yet, underexploited potential for automating the correlation of proxy timeseries, ensuring reproducibility and deriving confidence bands associated with the alignment procedure.

This project aims at developing an automated algorithm for stratigraphic correlation and deploying the first graphical user interface (GUI) to perform probabilistic alignment of palaeoclimate records.
Tasks
The successful applicant will:
1) develop an improved Markov Chain Monte Carlo alignment algorithm that models alignments based on multiple proxy signals and incorporates prior knowledge on the depositional history of the climate archives used for correlation;
2) design a dedicated GUI software to facilitate the usability of the algorithm. The new algorithm and related GUI will provide an essential tool to construct robust chronologies for climate archives with poor independent age control and will increase the accessibility of probabilistic alignment methods to the wide palaeoclimate community.
Requirements
Eligible candidates:
* Must have a PhD in Earth Science, Geological Science, Applied Mathematics, Computer Science, or similar;
* A background in Mathematics, Bayesian Statistics, and Stochastic Processes is desirable;
* A strong programming skills and prior research experience in MCMC techniques and Bayesian inverse modelling would be a significant advantage.

Applicants must also have proven experience of publishing high-quality research articles. They must be highly motivated and should have excellent time management, organisational and communication skills, and be able to work well as part of a team.
Applications
Further information on the role and application particulars can be found here: https://www.jobs.cam.ac.uk/job/32299/
Application deadline
Contact email
fm476@cam.ac.uk