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Research Fellow in Palaeoecology

Coventry University Group (CUG) - Research Centre for Agroecology, Water and Resilience (CAWR)

Location: Coventry
Salary: £38,784 to £42,254
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 21st October 2026
Closes: 3rd November 2026
Job Ref: 3819

Competitive starting salary range from £38,784 up to £42,254 per annum (dependent upon experience) with the potential to progress. A discretionary range for candidates with exceptional experience can be discussed/considered.

Fixed Term for 24 Months

Our Mission

Coventry University is a global Education Group that empowers students and communities to transform their lives and society through teaching, learning, research, and enterprise.

 An ambitious and innovative university, our research is designed to have real-world impact on society and tackle global challenges through our 13 challenge-led, interdisciplinary research centres. We enable high performing research teams and future research leaders to thrive and make an impact locally, regionally, nationally, and globally

The Role

As Post-Doctoral Research Fellow within the Centre for Agroecology, Water and Resilience (CAWR) you will play a key role in the AHRC-funded ARTEMIS project, which aims to uncover the untold stories of Greek rural communities by generating an integrated human-environment narrative that brings the rural heart of ancient Greece to light. Working closely with the project co-lead based in the Climate and Environmental Change research cluster at CAWR, and with colleagues at the Universities of Birmingham (UK), Patras (Greece), and Innsbruck (Austria), you will contribute to palaeoenvironmental reconstruction, pollen-based land-cover modelling, and integration of results with archaeological data to inform understanding of Holocene human-environment relationships in East Attica, Greece. 

In this role you will contribute to fieldwork in East Attica to retrieve sediment cores for analysis, and to conduct vegetation surveys and modern pollen sampling to enable estimation of Relative Pollen Productivity (RPP) for Greek taxa. You will lead laboratory analyses, including pollen, non-pollen palynomorph, and microscopic charcoal, of both modern and palaeoenvironmental samples. In collaboration with post-doctoral researchers based at Birmingham and Patras, you will be responsible for selecting and submitting material for radiocarbon dating and developing age-depth models for the sediment sequences. You will also have the opportunity to contribute to estimation of RPP for Greek taxa, and to develop your skills in quantitative land-cover modelling, including both the Landscape Reconstruction Algorithm (LRA) and the Multiple Scenario Approach (MSA). 

The role will involve applying innovative research methods, expanding the research portfolio through high-quality publications, and building strong internal and external networks to support knowledge exchange, future collaborations, and funding opportunities.

Qualifications

PhD (or equivalent) demonstrating an ability to carry-out independent research with a 1st Class/2.1 Degree in an appropriate subject such as Geography, Environmental Science, Earth Sciences, Botany, or Archaeology.

Our Successful Candidate

You will be a highly motivated and experienced Research Fellow with demonstrable expert knowledge, understanding and prior experience of palynology, palaeoecology, and palaeo environmental reconstruction. 

You will have advanced knowledge of research methods and techniques with demonstratable adherence to all regulations, as well as the ability to develop research objectives, projects, and proposals for your own and joint research. 

You will have expertise and experience in palaeoenvironmental fieldwork, including sediment coring, and in pollen, non-pollen palynomorph, and microscopic charcoal analysis. You should have experience of selecting and submitting suitable samples for radiocarbon dating, and be willing to contribute to fieldwork for RPP estimation. Experience of age-depth model construction and sedimentological analyses including loss-on-ignition and particle size analysis would be beneficial, as would GIS and numerical data analysis skills.

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