Diatoms of North AmericaPosition 1. Characterising lake responses to climate extremes using high-frequency sensor data
We are seeking an enthusiastic and highly motivated student for a fully funded PhD project using high-frequency sensor data to understand lake ecosystem responses to climate extremes. Lakes are increasingly exposed to extreme climate events (e.g., intense storms, droughts), yet typical monitoring (manual to fortnightly) often prevents a robust understanding of the response and recovery of lake ecosystems following these events. We aim to analyse automated high-frequency sensor data from profiling buoys in lakes across Aotearoa New Zealand to characterise changes in lake ecosystem structure and function following some of the most extreme climate events observed in New Zealand (e.g., Cyclone Gabrielle).
Background: Traditionally, lake monitoring has been limited to weekly or fortnightly monitoring. While this approach has been extremely successful for understanding long-term patterns in lake ecosystems, it does not capture the high temporal variability in freshwater ecosystem processes following extreme events.
About the project: The successful candidate will analyse high-frequency sensor data from several lakes across New Zealand to quantify lake ecosystem responses to climate disturbances. This will involve characterising ecosystem responses across different lake types.
About the candidate: We are looking for a candidate with a background in quantitative lake ecology and data analytics. The ideal candidate would be proficient in R and understand advanced data manipulation and statistical time series techniques. The candidate will be expected to be skilled in handling and analysing large, high-resolution continuous datasets, and applying advanced data analysis techniques to quantify rapid ecosystem changes. The project may also involve developing and validating predictive models to forecast future lake responses to climate extremes.
What we offer: The successful candidate will be based at University of Waikato under the supervision of Associate Professor Deniz Özkundakci and Associate Professor Jamie Howarth at Victoria University of Wellington. They will work closely with Dr Whitney Woelmer (University of Waikato). They will be supported by the wider team both in the field and when using high-frequency buoy data across the country. We offer a competitive stipend and cover all fees ($35,000 stipend per year + fees). Being based in Hamilton provides an ideal balance for PhD students, with access to world-class research facilities at the University of Waikato, a diverse cultural community, a nearby national park, and world-class surf in Raglan, all within a short drive.
Application: Candidates should submit an application to Deniz Ozkundakci . This must include a complete CV (including academic transcripts) and a letter containing the following information - motivation for applying, research interests and experience, and the name and contact details of two or more academic referees is required. Applications received on or before 15 November 2024 will be considered. The successful applicant will be expected to take up the position no later than the March 2025.
Position 2. Investigating lake responses to extreme weather events using high-resolution paleoenvironmental reconstructions
Climate change is already increasing the frequency and intensity of extreme weather events, such as storms and droughts, and these effects are forecast to worsen under future climate projections. For example, extreme rainfall caused by ex-tropical cyclones dramatically increases catchment runoff and causes erosion, delivering high sediment and nutrient loads to lake ecosystems. However, little is known about how lake ecosystems respond to these pulse disturbances, limiting attempts to forecast the impact of future climate scenarios on lakes in Aotearoa-New Zealand. We seek an enthusiastic and highly motivated student for a fully funded PhD project using paleoenvironmental reconstruction to understand lake ecosystem responses to extreme weather events.
Background: Traditional lake monitoring is usually limited to timeframes that span a few decades and rarely capture lake ecosystems responding to extreme weather events. Recent advances in using sedimentary environmental DNA (eDNA) to track ecosystem change in lake sediment cores with high-resolution chronologies now provide an unprecedented opportunity to extend monitoring of lake ecosystems deep into the past to resolve how they respond to past extreme weather events.
About the project: The successful candidate will analyse sediment cores from a series of lakes across Aotearoa-New Zealand, to quantify lake ecosystem responses to past extreme weather events. This will involve a combination of fieldwork, laboratory work, analysis of large datasets, and potentially numerical modelling.
About the candidate: We are seeking a candidate with a background in paleoenvironmental reconstruction and/or lake ecology. The ideal candidate would have previous laboratory experience, preferably in generating and analysing eDNA data, and proficiency in R. The project may also involve developing and validating predictive models to forecast future lake responses to climate extremes, so numerical modelling experience would also be welcomed.
What we offer: The successful candidate will be based at Te Herenga Waka – Victoria University of Wellington under the supervision of Associate Professor Jamie Howarth, and Professor Susie Wood (Lincoln University). This wider team will support the successful candidate in their fieldwork, laboratory work, data analysis and modelling endeavours. We offer a competitive funding package that covers fees and living costs ($35,000 stipend per year + fees). The successful candidate will be based in Wellington, Aotearoa-New Zealand’s capital city, offering an ideal balance of cultural amenities and a superb natural environment right on your doorstep.
Application: Candidates should apply here. Please include a complete CV (including academic transcripts) and a letter containing the following information - motivation for applying, research interests and experience, and the name and contact details of two or more academic referees. Applications received on or before 15 November 2024 will be considered. The successful applicant will be expected to take up the position no later than March 2025.
