LakeCast: Enhancing lake ecosystem management with multisource integrated data and ecological forecasts

About this opportunity

We are seeking two enthusiastic and highly motivated students for a fully funded PhD project to develop ecological forecasts to serve as decision support tools as part of our recently funded programme ‘LakeCast’ project. Lakes are under increasing pressure from multiple stressors, yet we lack methods pre-emptively identify lake water quality impairments such as algal blooms, often impeding management efforts. By leveraging abundant water-quality data and advances in sensor fusion and ecological forecasting theory, we will develop accurate forecasts and actionable insights for regional councils and iwi.

We are recruiting a cohort of two PhD students who will work closely together on this project, each with a distinct focus. One position will focus largely on developing novel machine learning algorithms using diverse high-frequency sensor datasets and will be mentored by engineers and computer scientists at the University of Waikato. The second position will be centered on lake ecology, using data science techniques to develop statistical and mechanistic modelling approaches, and will be mentored by freshwater ecologists and computational limnologists. The students will form part of a collaborative team to develop actionable decision-making tools to support freshwater management.

Location

Hamilton Campus

Scholarship Value

We offer a competitive stipend and cover all fees (NZ$35,000 stipend + tuition fees per year for three years)

The general Higher Degrees admission criteria apply.

About the candidate (PhD in Engineering):

• We are looking for a candidate with a background 
  in sensing, measurement, and applied machine learning. The ideal candidate would be proficient in Python and C, and understand sensor data acquisition and preprocessing, and 
  machine learning modelling methods.
• Candidates must have a relevant Bachelor of Engineering (Honours) or Master by Research degree in Electrical and Electronics, or Electronics, or Software.

About the candidate (PhD in Science):

• We are looking for a candidate with a background in 
  data science and lake ecology.
• The ideal candidate would also be proficient in R (or 
  comparable software) and understand data manipulation and statistical, process-based, or machine learning modelling methods.
• Candidates must have a relevant Bachelor’s degree 
  with honours or Master’s degree.