PhD: PhD in Micropalaeontology for the DFG Project “Ocean Life on the brink of extinction: Quantifying the collapse of marine ecosystems during the Permo-Triassic climate crisis”

The candidate will investigate changes in the abundances of microfossils, more specifically foraminifera, across the Permian-Triassic transition using newly collected material. Depending on the applicants experience and interests this can, however, be a different microfossil group of organisms (e.g., ostracods). Changes in the composition of microfossils provides information on changes in the eukaryote community that can also be used to infer the ecological impacts of environmental changes on marine ecosystems. It would be preferred if the candidate could also analyse microfossil record by integrating multivariate statistical methods. The candidate will deliver regular progress reports, contribute to research seminars, write research papers, and present research results at international conferences. Experiences and skills gained will be of potential use in a variety of careers in research, academia and industry.

The project will provide training in collecting, processing and analysing fossil records. The successful applicant will also have the opportunity of undertaking a range of skills-based modules through the postgraduate training programme at the Universität Hamburg, including having the further development of writing and presentations skills. The successful candidate will also benefit from interactions with the entire Emmy Noether research team and staff at the Universität Hamburg.

We are looking for a candidate who has demonstrable interests, skills and experience in palaeontology/palaeoecology, with evidence of having successfully undertaken a geoscience research project at the undergraduate or master’s level. Additional experience of one or more of the following would be an advantage: taxonomy of a microfossils or another invertebrates, working in a research lab, geological fieldwork, multivariate statistics, computer programming in R, Matlab or Python. The applicant should be fluent in English and engaged in teamwork. German language fluency is not required, but a willingness to learn German is expected.