approaches for quantifying and identifying microorganisms in water and wastewater treatment
Job No.: 648559
Location: Clayton campus
Employment Type: Full-time
Duration: 3.5-year fixed-term appointment
Remuneration: $30,000 p.a 3.5 years full-time rate (pro-rata) 2023 rate
A full scholarship is available for a PhD student to conduct research on development of fluorescence-based methods, flow cytometry, automated cell imagery, and artificial intelligence for identifying and quantifying microorganisms for large scale testing at target treatment trains. The research will be conducted in Dr Arash Zamyadi's group (within Environmental and Public Health Microbiology Laboratories, Living Lab) in the Department of Civil Engineering, in collaboration with other research groups at Monash, national research institutes and overseas, and Australian water industry including Melbourne Water and Water Research Australia.
Assessment of water and wastewater treatment efficacy will require extensive analysis of microbial viability and microbial quantification/taxonomic identification. Cell viability assessment capabilities will require development of fluorescence-based methods. Novel quantification/identification capabilities will be developed using automated analysis with cell imagery, flow cytometry and artificial intelligence for large scale testing at target treatment trains (including but not limited to treatment technologies that manage algal blooms). This project hypothesises that a supervised and knowledge-guided machine learning approach can be used to identify microbes accurately and rapidly within manufactured water samples using different analytical platforms (optical microscopy, fluorescence microscopy and imaging flow cytometry). The PhD project objectives are to explore (1) fluorescence-based approaches for determining microbial viability and activity in water and wastewater, and (2) machine learning approaches for quantifying and identifying microorganisms.
A strong background in environmental microbiology, experience in using fluorescence-based methods, and flow cytometry is essential. Additional experience in cell imagery, coding and artificial intelligence is required. Applicants must show excellent communication and inter-personal skills, and the ability to conduct self-motivated research. They should have research- based Honours or Masters Degree (or equivalent) in the relevant research areas and have a record of publishing their research in mainstream scientific journals.
Note: applicants who already hold a PhD will not be considered.
Shortlisted candidates will be interviewed, over Zoom if necessary. The interviews will be conducted in English.
Applicants will be considered provided that they fulfil the criteria for PhD admission at Monash University and demonstrate excellent research capability. Details of the relevant requirements are available at www. monash.edu/graduate- research/future-students/apply.
Expression of Interest
Please submit this Expression of Interest (EOI) form forms.gle/Mxj9cfzzcUCiAekT6, preferably in the form of a single PDF attachment.
EOIs shall comprise
Dr Arash Zamyadi, Senior Lecturer, Civil Engineering, [email protected]
Applications will close once a suitable candidate has been identified
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