Primary supervisor
Sarah GoodwinCo-supervisors
- Hao Wang
- Terrence Mak
- Tim Dwyer
- Yidan Zhang
- Sam Rye (BPD)
- Markus Wagner (FIT)
- Amal Al Shardy (FIT)
- Annelieke de Wit (Monash Energy Institute)
Please note this advert is for a Summer Research Internship. It is not currently an advertisement for an honours or masters thesis project.
Please note you can ONLY apply for this internship via the internship application form.
Internship Project: https://www.monash.edu/study/fees-scholarships/scholarships/summer-winter
Aim/outline
Monash University was one of the first universities in Australia to pledge a Net Zero goal. The Net Zero Initiative is ambitious and well under way. This requires deep emission cuts across all greenhouse gases across the University. The University has invested heavily in solar and wind (purchase of wind farm) generation, and is currently in a phase of “electrifying” the campus to move away from a heavy dependency on gas and investing in infrastructure for electric vehicle (EV) and bicycle charging.
The campus forms a small city in its mixture of building and land use - with some buildings purely for research (some with large and heavy consumption machinery, such as a wind turbine), others heavily used in semester for teaching, some busy during the evenings and weekends, the theatre and sports facilities for instance, and a large residential base throughout the year (reduced in the semester breaks), with retail and food outlets and natural reserves. Older buildings are being retrofitted with new meters, sensors and more.
This internship seeks to start a very strong collaboration between Monash academics and Monash Buildings and Property to ensure students are gaining the needed experience ready for an energy sector in transition.
The first cohort of students will focus on data analytics, optimisation and visualisation.
Required knowledge
Ideally 3rd or final year UG or Masters level.
Experience of data analytics, optimisation, data visualisation or visual analytics.
Competent programmer (tech stack to be confirmed).
Basic knowledge of quantitative and qualitative research methods useful.
Interest in energy, electrification, or digital twins.