The ‘Rewilding” project is trialling a new mode of industry-led cross-sector research in exploring later prehistoric wildlife and its relevance to contemporary ecological debates. The project is led by Oxford Archaeology (OA) in partnership with the Universities of Oxford, Exeter and Toulouse, the Archaeology Data Service, Historic England and Knepp Castle Estate. The current nature conservation concept of “rewilding” will be recast for archaeological purposes in order to reveal the “wonder and enchantment” of wildlife in the Bronze and Iron Ages – a key period in the transition from ‘wild’ to “farmed” landscapes in Britain. The ‘blank spaces’ study is one of a series of studies which will build an original multi-stranded toolkit for investigating archaeological wildlife. The postholder – a palynologist with strong computational skills – will work with lead investigator Dr Anwen Cooper, palaeoenvironmental experts at OA, and Professor Mike Charles, University of Oxford. They will also assist in the management of this study. The postholder will be based at OA and will have access to lab space and equipment at the School of Archaeology, Oxford.
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[Website Oxford Archaeology]
Cette offre d'emploi s'inscrit dans le cadre du projet ANR STEPABILITY (Steppe Sustainability in a Changing World) visant à comprendre la résilience des écosystèmes steppiques de la région circum-Caspienne face à l'intensification des pratiques agro-pastorales au cours de l'Age du Bronze. Dans ce cadre, les études archébotaniques viseront à reconstituer l'évolution des écosystèmes steppiques, des pratiques agricoles et des dynamiques de peuplement de la région.
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[Site web CNRS]
Radical changes in the Earth’s biome have occurred over the past 30,000 years, with consequent changes in species ranges and connectivity. How can we best model species dynamics over thousands of years of ecological change? And what are the main environmental drivers underlying these dynamics? There is now a wealth of historic and prehistoric records documenting these processes, including pollen and fossil records, ancient genomes and sedimentary DNA, but a lack of tools limit the insights that can be derived from these records. Our ERC-funded research project - called Spatiotemporal Analytical Modelling for Paleobiology (STAMP) – will serve to link these disparate types of paleobiological records with the methodological tools of spatiotemporal process analysis. As proof of principle, we will analyze various types of paleobiological datasets from northern Eurasia and northwest North America. The postdoctoral fellow will work on one of the first work packages of this project, particularly focusing on megafauna range dynamics in the Arctic and taiga. The first year of the postdoctoral project will involve a period of co-supervision with Dr. Yucheng Wang (University of Cambridge) – an expert in sedimentary genomics. The first focus of the postdoctoral fellow job will involve computationally collecting and assembling a database of paleobiological records from select megafauna species of the Arctic and taiga.
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[Website University of Copenhagen]
Applications are invited for a Research Assistant in Cultural Heritage with a particular emphasis on the impact of climate change on historical sites in Istanbul in Turkey as part of the UKRI Arts and Humanity Research Council (AHRC) project entitled "Developing a novel Climate change Risk Assessment Framework for cultural heritage in Turkey- Phase II (CRAFT2)". The successful applicant will be expected to will design and carry out a survey to measure the public's level of awareness about climate change-related impacts on heritage sites where they live and the level of knowledge of the value of the surrounding cultural heritage. The study will also assess the views on the relationship between vulnerability level and the conservation measures of the cultural heritage. The study will include both qualitative and quantitative methods of research. The quantitative data will be analysed via Statistical Package for the Social Sciences, and the qualitative data will be analysed using inductive data analysis. The spatial distribution will be mapped by using GIS programs. The survey results will be used to inform discussion on policymaking.
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[Website Durham University]