Past internship opportunitites

Supervisors:

Pauline Barmby, Physics & Astronomy & Jinfei Wang, Geography

Description:

Galaxies include many different components – stars, gas, dust, planets and black holes among others – and disentangling these components is important for understanding their relationships within a galactic ‘ecosystem’. Our research collaboration has used machine learning to classify galaxy components and stellar age in Hubble Space Telescope images. This summer project involves extending our methods to new images from the James Webb Space Telescope and to a comparison between Hubble and JWST. Our goal is to learn how well image-analysis methods derived from geographic information systems research can identify the different components of galaxies.

Required qualifications:

The intern needs to be comfortable with using computers to analyze numerical data, make graphs, and do calculations (eg, via coursework in statistics, data science, or other relevant areas). Familiarity with ArcGIS or QGIS would be an asset, as would familiarity with Python or R and their use in machine learning.

Supervisor:

Sean Shieh, Earth Sciences

Description:

Reidite is a high-pressure form of zircon (ZrSiO4) that is popular for age determination of terrestrial planets. Reidite can be found at impact sites or shocked meteorites but requires to be formed at high pressure and high temperature conditions. Furthermore, reidite was also reported to be stable at pressure greater than 7 GPa and high temperatures experimentally. However, recent shockwave study suggested the reidite synthesized pressure should be greater than 35 GPa. Since reidite is also regarded as a barometer, its appearance in the impact sites or meteorites can be used as an indicator for the peak pressure for impact events. Furthermore, the mechanical property such as strength of reidite plays an important role for the evolution of terrestrial planets. However, knowledge of the strength and deformation of the reidite is unclear. This project aims to exam the strength and deformation of reidite at high pressure and room temperature using lattice strain theory, together with viscoplastic self-consistent theory (VPSC) predictions.

Supervisors:

Ana Luisa Trejos, Electrical and Computer Engineering and Adam Sirek, Schulich School of Medicine & Dentistry

Description:

This project involves completing the engineering design of a wearable sensor system that can monitor the health of the musculoskeletal system of astronauts exposed to a reduced gravity environment.

Required Qualifications:

Undergraduate student in electrical, mechanical or mechatronics system engineering with preference given to students completing a dual degree in biomedical engineering.

Supervisor:

James Voogt, Geography

Description:

This summer research internship will support research using high resolution thermal imagery for urban climate applications. Work will include: 1) developing methods to use multi-viewing angle thermal imagery collected from airborne or drone platforms to characterize the complete exterior temperature characteristics of buildings. These temperatures will then be used in combination with building energy models to assess building heat loss and energy demand, 2) working with high resolution thermal and lidar data to characterize the three-dimensional thermal structure of urban residential neighbourhoods, 3) using remote sensing and GIS methods to support identification of heat vulnerability in London.

Required Qualifications:

Applicants should have some knowledge and experience with remote sensing and/or GIS software such as ArcGIS, QGIS, and the ability to work with numerical data sets and remotely sensed imagery. Knowledge of computer programming using Python, Matlab, RStudio or other programming languages would be considered an asset. The position should be suitable for students with academic backgrounds from Physical Geography, Geographic Information Science, Environmental Science, Environmental Engineering or related fields. Any academic course work or research experience related to urban climate or more generally microclimates, atmospheric science, remote sensing, climate adaptation, urban environments or landscape architecture would provide useful background.

Supervisor:

Dr. Pauline Barmby, Physics and Astronomy

Description:

Our team has used the Canadian UVIT telescope on the Indian Astrosat satellite to observe low-surface-brightness spiral galaxies. These ghostly galaxies are difficult to observe and even more difficult to understand: despite having plenty of interstellar gas, they are not converting this gas to stars; despite having few young stars, they have blue colours. Combining Astrosat images of the ultraviolet light emitted by these galaxies with data from other telescopes will help us to understand the current and past properties of these galaxies and others.

Required qualifications:

Applicants should have some academic background in physics, astronomy, engineering, or computer science. Ideally they will have research or coursework experience with image analysis (eg in physics, astronomy, remote sensing, computer science or other fields) and be comfortable with using Python and Linux.

Supervisors:

Adam Sirek & Valerie Oosterveld

Description:

Galaxies include many different components – stars, gas, dust, planets and black holes among others – and disentangling these components is important for understanding their relationships within a galactic ‘ecosystem’. Our research collaboration has used machine learning to classify galaxy components and stellar age in Hubble Space Telescope images. This summer project involves extending our methods to new images from the James Webb Space Telescope and to a comparison between Hubble and JWST. Our goal is to learn how well image-analysis methods derived from geographic information systems research can identify the different components of galaxies.

Required qualifications:

The intern needs to be comfortable with using computers to analyze numerical data, make graphs, and do calculations (eg, via coursework in statistics, data science, or other relevant areas). Familiarity with ArcGIS or QGIS would be an asset, as would familiarity with Python or R and their use in machine learning.

Supervisor:

Adam Sirek & Ana Luisa Trejos

Description:

Novel technologies to monitor, support and maintain crew health are critical to human exploration in cis-lunar space. A major focus of monitoring crew health and performance will be decisions and technologies surrounding what measures will be important and how they will be collected. Vital signs are a commonly collected and important value for decision making by clinicians. While commonplace terrestrially, collecting vital signs in microgravity or variable gravity continues to be a challenge. Discussions about what vital signs are needed, on what frequency and how to collect them remain a topic of discussion in the biomedical engineering field.

For this project, intern(s) [1 med, 1 eng] will perform a tech watch style survey of available wearable bio-monitoring devices and propose a series of appropriate devices for potential cis-lunar missions. Furthermore, in the final report, the team will discuss the timescales and methods in which vitals will be collected and used by the crew medical officer and terrestrial based flight surgeons.

Engineering Intern Required Qualifications:

Mechatronics (ideal), Mechanical or Electrical Engineering student who has completed at least 2nd year. A dual degree with BME would be a significant plus.

Med Intern Required Qualifications:

UGME or PGME (medical student or resident)

Supervisors:

Els Peeters & Jan Cami

Description:

We have recently witnessed the successful launch and deployment of the James Webb Space Telescope (JWST). Hailed as the bigger and vastly more sensitive successor to the HST, JWST will similarly inspire the general public and have researchers develop the most innovative approaches to process and analyze observations of unprecedented quality to study the Universe near and far.

JWST observations will be dominated by infrared (IR) emission from large carbonaceous molecules (polycyclic aromatic hydrocarbons, PAHs). This emission encodes a large amount of information about the physical and chemical environments in which they reside and is a powerful messenger to study astrophysical processes such as star and planet formation and galaxy evolution. The best observations to date of astronomical PAH sources yield spectra averaged over regions with vastly different properties, thus greatly confusing their interpretation. JWST’s incredible spatial resolution and sensitivity will disentangle these regions and allow us unprecedented views on PAH characteristics on small spatial scales.

The first few hundred hours of science time with JWST will be used to carry out 13 so-called Early Release Science (ERS) programs. The ERS programs represent a new category of scientific investigation, with two key pillars: their scientific merit on the one hand, and the delivery of so-called Highly- Processed Data Products and Science Enabling Products (SEPs) on the other hand - tools that will help other researchers to create better observing proposals, help to analyze, interpret, and disseminate the resulting data, and thus increase the scientific return of the entire mission. I am leading one of the 13 successful ERS programs: ID 1288 “Stellar Feedback of massive stars" (https://jwst-ism.org). We will observe a very popular astronomical object, the Orion Bar.

Two summer projects are available:

1) the student will participate in the development of these science enabling products (i.e. the scientific development, programming, and testing) and 2) the student will study infrared observations obtained with the Spitzer Space Telescope and analyze variations in the spectral features of PAHs to help us understand future JWST observations.

Intern Required Qualifications:

The ideal candidate has a background in physics, astronomy, math or computer science, and extensive programming experience in Python. Experience with data analysis or collaborative software development (e.g. using github) is an asset, and we also expect the interns to be team players.

Supervisor:

Peter Brown

Description:

This project will perform the first detailed reconnaissance of a recently developed database comprising multi-station measurements of the faintest meteors ever observed. The data were gathered using automated EMCCD cameras deployed near Western University. The purpose is to examine the physical behaviour of meteors as a function of their orbital characteristics, with emphasis on statistical correlations of meteoroid strength with orbit type. More broadly correlations will be examined of ablation behaviour (begin and end heights, light curve shape etc) as a function of mass, orbits and speed. The outcome of this project will be the first meta-analysis correlating physical properties of mm-sized meteoroids with their orbit types, providing insight into the broad physical properties of a large sample of asteroids and comets.

Intern Required Qualifications:

The ideal candidate will have extensive programming experience in Python and a math/physics or computing background. Experience with analysis of large datasets and associated analysis tools an asset.

Supervisor:

Jayshri Sabarinathan

Description:

Hyperspectral camera development for remote sensing from micro-satellites – involves embedded systems and circuit hardware expertise/interest and optical imaging instrumentation development; industry partners are involved in project.

Intern Required Qualifications:

1-2 students preferably Electrical Engineering or related area with interest/expertise in building circuit hardware and/or optical imaging instrumentation. The hardware will be early prototypes of space compatible instrumentation that for either satellites or lunar rover operation.

Supervisor:

James Voogt

Description:

Dr. James Voogt is seeking a student with interests in remote sensing, Geographic Information Science and/or microclimate/micrometeorology to help construct and analyze a data set of coupled high resolution ground-based thermal imagery and lidar data for two suburban neighbourhood study sites in Salt Lake City, UT. This dataset provides high resolution urban structure and temperature information that will be used to re-construct a detailed three-dimensional surface of the thermal environment at these sites. Combined with other available measurements of air and surface temperature from the project it will provide a unique dataset for assessing heat loading on pedestrians in urban neighbourhoods, the impacts of tree shading on urban microclimates, and the relationship between the full three-dimensional temperature environment of urban neighbourhoods with that observed from airborne or satellite-based sensors.

Intern Required Qualifications:

The student should have some experience with use of remote sensing data analysis, ideally related to thermal infrared wavelengths, lidar data analysis and some skills in MATLAB or equivalent scripting/programming skills. The student will collaborate with other graduate students and scientists on the project from Canada and the US. Data from the project may be used as a basis for a student thesis if desired.