Current Opportunities
We are always interested in hearing from prospective students and postdocs interested in our current activities! Please get in touch.
Current Openings:
Summer Research Opportunity for Undergraduate Students:
Arctic Oceanography & Climate Models
We are seeking an enthusiastic and motivated undergraduate student interested in a research position in our group this upcoming summer (16 consecutive weeks between May 1 and Aug 31 2024).
The Arctic Ocean is a unique environment that is changing faster than anywhere else on Earth. Climate models, our only tool to extrapolate into possible future climates, exhibit systematic bias in their representation of these changes, failing, for example, to accurately reproduce the observed sea ice evolution (Notz et al. 2020), upper Arctic Ocean properties (Muilwijk et al. 2023), as well as water properties of deeper layers (Heuzé et al. 2023). It is important to investigate how these biases are affected by the representation of different processes in these models in order to better understand the sources of model biases and to suggest ways they can be addressed in order to build more robust and useful climate models in the future.
In this project, we will examine the representation of ocean mixing processes in a climate model of the Arctic Ocean. We will diagnose the strength, spatial variation, and seasonality of ocean mixing in the model, and quantify how different mixing processes each contribute to overall mixing strength and variability. Finally, we will examine the sensitivity of these contributions via the analysis of a set of model experiments in which the ways ocean mixing is prescribed in the model are systematically varied. For more information about the model and these experiments, see this poster produced by a former undergraduate research student in our group. This project serves as a demonstration-of-concept for a larger international effort that seeks to compare the representation of ocean mixing processes in the Arctic Ocean across a suite of state-of-the-art climate models and thus has the potential to be of significant interest and value to the climate modelling community.
The project will offer the opportunity to work with the output of climate model simulations using coding software/languages such as MATLAB and/or Python. The student will develop metrics and visualizations that evaluate ocean mixing in the model from different processes and illustrate similarities and differences in the modelled Arctic state and its response to climate change for different mixing prescriptions. As part of the appointment, the student will engage with our research group and research in the Department of Earth, Ocean & Atmospheric Sciences at large, thus gaining exposure to cutting-edge Earth Science research in diverse forms.
Offer of a position is contingent on the award of an NSERC Undergraduate Student Research Award (USRA) (for Canadian and permanent residents) or a Science Undergraduate Research Experience (SURE) Award (for UBC Vancouver BSc students). All information on student eligibility and award conditions can be found here and here.
The position is paid at a minimum rate of $9,755,20 for the 16-week appointment.
The project requires coding skills relevant to working with large datasets of numerical model output. Experience using MATLAB is a significant asset in order to build upon existing tools used in the group.
If interested or to learn more, please contact Stephanie Waterman at swaterman@eoas.ubc.ca. Note that to be considered, an online application must be completed and submitted to the Department of Earth, Ocean & Atmospheric Sciences by Friday March 8 2024. For the application, a copy of your official transcript(s) must be uploaded.
The University of British Columbia is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.
Arctic Oceanography & Climate Models
We are seeking an enthusiastic and motivated undergraduate student interested in a research position in our group this upcoming summer (16 consecutive weeks between May 1 and Aug 31 2024).
The Arctic Ocean is a unique environment that is changing faster than anywhere else on Earth. Climate models, our only tool to extrapolate into possible future climates, exhibit systematic bias in their representation of these changes, failing, for example, to accurately reproduce the observed sea ice evolution (Notz et al. 2020), upper Arctic Ocean properties (Muilwijk et al. 2023), as well as water properties of deeper layers (Heuzé et al. 2023). It is important to investigate how these biases are affected by the representation of different processes in these models in order to better understand the sources of model biases and to suggest ways they can be addressed in order to build more robust and useful climate models in the future.
In this project, we will examine the representation of ocean mixing processes in a climate model of the Arctic Ocean. We will diagnose the strength, spatial variation, and seasonality of ocean mixing in the model, and quantify how different mixing processes each contribute to overall mixing strength and variability. Finally, we will examine the sensitivity of these contributions via the analysis of a set of model experiments in which the ways ocean mixing is prescribed in the model are systematically varied. For more information about the model and these experiments, see this poster produced by a former undergraduate research student in our group. This project serves as a demonstration-of-concept for a larger international effort that seeks to compare the representation of ocean mixing processes in the Arctic Ocean across a suite of state-of-the-art climate models and thus has the potential to be of significant interest and value to the climate modelling community.
The project will offer the opportunity to work with the output of climate model simulations using coding software/languages such as MATLAB and/or Python. The student will develop metrics and visualizations that evaluate ocean mixing in the model from different processes and illustrate similarities and differences in the modelled Arctic state and its response to climate change for different mixing prescriptions. As part of the appointment, the student will engage with our research group and research in the Department of Earth, Ocean & Atmospheric Sciences at large, thus gaining exposure to cutting-edge Earth Science research in diverse forms.
Offer of a position is contingent on the award of an NSERC Undergraduate Student Research Award (USRA) (for Canadian and permanent residents) or a Science Undergraduate Research Experience (SURE) Award (for UBC Vancouver BSc students). All information on student eligibility and award conditions can be found here and here.
The position is paid at a minimum rate of $9,755,20 for the 16-week appointment.
The project requires coding skills relevant to working with large datasets of numerical model output. Experience using MATLAB is a significant asset in order to build upon existing tools used in the group.
If interested or to learn more, please contact Stephanie Waterman at swaterman@eoas.ubc.ca. Note that to be considered, an online application must be completed and submitted to the Department of Earth, Ocean & Atmospheric Sciences by Friday March 8 2024. For the application, a copy of your official transcript(s) must be uploaded.
The University of British Columbia is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.