PhD PROJECTS

ACEAS Student Projects and Scholarships

From the second half of 2021, a number of PhD research projects related to the research programs of the Centre will be advertised here and on Australian university partner web sites for proposed commencement in January 2022 and beyond.  Applicants will be able to apply for Stipend Scholarships and fee waivers from the participating Australian Universities or from other sources, as well as Top-up Scholarships from ACEAS.

It is anticipated that many PhD graduates will have careers in industry and government, as well as in research and academia.  And, so, ACEAS is committed to training PhD students in their specialist area of research as well as in Antarctic science broadly plus Antarctic policy, governance, and law. The research of ACEAS will have particular focus on end-user engagement and early career researchers will be trained in communicating with those groups and the public through the media (including social media).

If you are interested in undertaking a PhD with ACEAS, please check this page regularly to look for advertised opportunities or contact a relevant supervisor directly.

PhD Project - Long-term changes of phytoplankton in the Southern Ocean

Program 1/Program 3 I Curtin University

The proposed PhD project which is supported by a PhD stipend from Curtin University will use multi-decadal records of satellite observations in search of decadal signals and their connection with Southern Ocean dynamics and large-scale climate drivers (like El Nino/La Nina). Such analyses are necessary to ultimately understand long-term changes in the ecosystem of this key yet remote ocean.

>20-year records of satellite-derived physical parameters (sea-surface temperature, wind speed and sea-surface height) and biological parameters (phytoplankton chlorophyll concentration) are available at the scale of the entire Southern Ocean. These parameters plus outputs of ocean models will be analysed in search of temporal signals and relationships, using statistical and/or machine learning techniques. This information will be used to assess the impact of various scenarios of change in the physical environment on future changes of phytoplankton.

Supervisor: Prof. David Antoine

Co-supervisors: Prof. Pete Strutton (University of Tasmania) and A/Prof. Alex Sen Gupta (University of New South Wales)