Full-time: 35 hours per week
Fixed-term: from January 2027 until 31st December 2028
The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area.
The University is part of alocal communityand a contributor toglobal thinking,progressand research. In Edinburgh, you are in one of the world’s most attractive cities with active arts and social sectors, while working in aUniversitythat has made significant contributions to society, medicine,physicsand teaching for over four centuries. Our people have helped create the modern world and are working on more ground-breaking technologies and practices.
The Opportunity:
We seek an interdisciplinary scientist to join our international team studying the evolution of brains, intelligence, and cognition over deep time. Our Deep Time Cognition team—funded by the Swedish Research Council—combines expertise in cognitive zoology, neurobiology, and palaeontology to understand how cognition and brains have evolved in concert over eons, and what has driven this evolution. By working together, we are creating an initial atlas of how neuroanatomy correlates with cognition expressed in behaviour. Drawing on these results we will then recreate the cognition of long extinct species, by making brain models based on fossils. This will make it possible to pinpoint cognitive changes in geological time, which can be correlated with major events in the history of Earth. More information on our team can be found here: www.deeptimecognition.lu.se.
The University of Edinburgh component of the team specializes in palaeontology and phylogenetics, and contributes data including CT scans of fossils and reconstructions of the brains of extinct species, and large phylogenetic trees and datasets for testing trends in evolution across genealogy and time. The Edinburgh team is led by Professor Stephen Brusatte (co-PI on the research grant).
The postdoctoral fellow will be a key member of the team. They will gather and synthesize data on the anatomy, size, and shape of the brains (via CT brain endocasts) for tetrapods across time (350+ million years of evolution), working closely with Brusatte and PhD students and external co-PI Lawrence Witmer (Ohio University) who have been gathering data on tetrapod subgroups (extinct dinosaurs, squamates, and amphibians). They will use Bayesian statistics to test for trends in brain size change over time and phylogeny, test for correlations between brain size and neuron counts in extant species, and make the most robust predictions for neuron counts in extinct species, including dinosaurs like Tyrannosaurus rex, contributing to an exciting current debate in the fields of cognitive zoology and palaeontology.
£41,064 to £48,822 per annum (Grade 7)
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Postdoctoral Research Associate in Cognitive Evolution over Deep Time employer: The University of Edinburgh
The University of Edinburgh offers a dynamic and supportive work environment for the Epigenetics Research Technician role, fostering collaboration and innovation in the field of biological sciences. With access to cutting-edge facilities and a commitment to employee development, staff are encouraged to grow their skills and advance their careers while contributing to impactful research projects. Located in the vibrant city of Edinburgh, employees enjoy a rich cultural experience alongside their professional journey.
Contact Details:
The University of Edinburgh Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Associate in Cognitive Evolution over Deep Time
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How to prepare for a job interview at The University of Edinburgh
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Brush up on your clinical knowledge, particularly in areas relevant to the role at The University of Edinburgh. Expect questions about diagnosis, treatment plans, and patient management. Be ready to discuss case studies or even do some role-playing with hypothetical patient scenarios for a more practical assessment.
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