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56 jobs at University of Southampton

Research Fellow (Postdoctoral) in Microbiology/Microbiome BJ) by Agreement in Southampton, Southampton, SO17
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Research Fellow in Evolutionary Biology BJ)

Job at University of Southampton in Southampton, Southampton, SO17

Applications are invited to work as a Postdoctoral Research Fellow in the Ecology and Evolution Group in School of Biological Sciences at the University of Southampton. The School of Biological Sciences hosts a diverse community of researchers aiming to tackle the world’s greatest life science challenges, from food security to prevention of disease to understanding the processes which regulate Earth’s biodiversity. You will work on a project attempting to understand the role of feeding performance in the deep time evolution of phenotype and ecological niche using the exceptional fossil and extant records echinoids. The post is funded as a part of the “UNLOCKING NEW HORIZONS – HOW FEEDING MORPHOLOGY AND PERFORMANCE IMPACTS ADAPTIVE EXPANSION IN DEEP TIME” collaborative grant between Southampton and Baylor University and funded by NERC and the NSF. The post will be managed by Dr. Jeff Thompson with regular meetings and with the team of Dr. Elizabeth Petsios. 

The fossil record represents an already-run natural experiment which we can use to understand the interaction between organismal function and performance, their environments, and the evolutionary process. Our trans-Atlantic team will test the hypothesis that changes in functional performance in echinoid (sea urchin) feeding morphology have regulated their morphological and ecological diversification over the last 300 million years of their evolution. Our approach combines large databases of 3D morphology and ecology, and statistical approaches to study macroecological patterns with analyses of morphological evolution using geometric morphometrics and phylogenetic comparative methods. 

Working as a part of an international team, together we will identify how performance regulates morphological evolution over millions of years of evolution. You will work closely with the mu-VIS X-Ray Imaging Centre at Southampton to generate micro-CT data and lead on 3D geometric morphometric analyses of museum specimens, and subsequent statistical and evolutionary analysis of morphometric data. This work will involve travel to museum collections in Europe and potentially further to identify fossil and extant specimens for scanning. You will hold a PhD in Evolutionary Biology, Palaeobiology, or a related field, and will be passionate about using 3D data to understand evolutionary questions. You will be based at the Highfield Campus in Southampton, a dynamic and vibrant city that caters for all.

As a university we aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and equality of opportunity. We believe that we can only truly meet our objectives if we are reflective of society, so we are passionate about creating a working environment in which you are free to bring your whole self to work.

With a generous holiday allowance as well as additional university closure days we are committed to supporting our staff and students and open to a flexible working approach.

If you wish to discuss the role in more detail, please email Dr. Jeff Thompson (j.r.thompson@soton.ac.uk).

*Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification.  The title of Research Fellow will be applied upon completion of PhD.  Prior to the qualification being awarded the title of Senior Research Assistant will be given. 

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Closing Date: 14 Apr 2025

Section: Education, Research & Enterprise

Salary: £36,130 per annum Full Time Fixed Term for 18 Months

ID 1151769 Sectors:
in Southampton, Southampton, England, SO17
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Research Fellow (Postdoctoral) in Microbiology/Microbiome BJ) by Agreement in Southampton, Southampton, SO17
Research Fellow Edge Computing for AI FP) by Agreement in Southampton, Southampton, SO17
Research Fellow in Machine Learning for Aeroelasticity A3) by Agreement in Southampton, Southampton, SO17
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