Algal microbiomes: diversity, structure and role in marine biotoxin production

Closing Date

31 October 2019

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

The Research Project

Marine phytoplankton drive global climate, form the base of marine food-webs, and can cause ecosystem disruption and collapse due to harmful algal blooms. In the ocean, phytoplankton interact with bacterial symbionts - their microbiomeswhich lab studies show are essential for their growth. However, we currently know almost nothing about phytoplankton microbiomes in natural marine systems, or how they interact to enhance the growth and toxicity of harmful algal blooms.

A PhD research opportunity is open for a talented graduate to investigate the diversity and function of natural phytoplankton microbiome, and how they enhance growth and toxicity of harmful dinoflagellates. The project combines microfluidics and single-cell genomics and microbial community profiling using NGS sequencing to characterise microbiome membership, structure and function directly from phytoplankton blooms. Using lab model co-culture techniques, the project will also determine how microbiomes are recruited by toxic phytoplankton, and examine their role in algal physiology and toxin production.

The project is supervised by Drs Christopher Bolch and Andrew Bridle and will be based in the Institute for Marine and Antarctic Studies (IMAS) at the University of Tasmania in Launceston. The project also includes collaboration with researchers in the Scotland (Scottish Association for Marine Science) and the USA (New York University).

Essential skills/experience

Graduates with a strong academic record in Biological or Health Sciences and a background/experience in molecular biology and/or microbiology are encouraged to apply. Applications for this PhD position are open to domestic and international students, provided the latter are competitive when applying for fee waiver scholarships.

Desirable skills/experience

Candidates with strong computing skills and experience of collecting and analysing next-generation-sequencing (NGS) data will be viewed favourably.

Assessment criteria

Applicants will be assessed and ranked according to the quality of their basis for entry research degree and institution, prior peer reviewed publications, academic awards, project-specific skills, training or relevant industry experience, referee’s reports and supervisory support.

Contact for more information

Please contact Christopher Bolch at for more information.