Announcing Summer 2021 Undergraduate Research Opportunities

News

Published: 19Feb2021

There are currently three undergraduate research funding opportunities for Summer 2021: SURA, NSERC USRA, and Schull Yang International Experience Awards. These allow students to engage in a full-time summer research activity, and to gain research experience in an exciting academic setting, while receiving financial support.  These are open to all B.Sc. and B.A. & Sc. students in the Faculty of Science. For Summer 2021, the Faculty of Science requires all project proposals to include a project the student can start and finish remotely. This does not preclude (also) submitting a proposal with in-person activities. Please continue reading for more details & note that the AOS available supervisors & projects are at the bottom of the page.


Science Undergraduate Research Awards (SURAs) are for both Canadian and international McGill students. The program covers all areas of science research (natural science and engineering, social science, and health/medical science). There are some SURAs reserved for research in Social Equity/Diversity/Social Justice, and for research at McGill’s Gault Nature Reserve (Mont-Saint-Hilaire, Quebec). The program supports projects with supervisors from the Faculty of Science, or a limited number of Faculty of Medicine departments (Anatomy & Cell Biology; Biochemistry; Microbiology & Immunology; Pharmacology & Therapeutics; Physiology). The minimum value of a SURA is $7000.
https://www.mcgill.ca/science/research/undergraduate-research/sura
Competition now open.

The NSERC Undergraduate Student Research Awards (USRA) in Universities program is similar but with some additional restrictions which include: students must be Canadian citizens and permanent residents; research must be in the field of natural science and engineering. The minimum value of an NSERC USRA in the Faculty of Science is $7500.
https://www.mcgill.ca/science/research/undergraduate-research/nserc (for applications with Faculty of Science professors)
Competition now open.

Schull Yang International Experience Awards in the Faculty of Science support Science students with full-time international summer undergraduate research experiences. Normally these must take place abroad; however, due to the Covid-19 pandemic, a different program will be offered this year. Students must apply with a remote project as "Plan A." Your proposal must be international in one or more significant way(s) that you must describe, other than travel. Award values will continue to reflect duration, but not estimated (travel) costs; target value is $7000, if for 16 weeks. Canadian supervisors are also permitted this year, including McGill professors.
https://www.mcgill.ca/science/research/undergraduate-research/schull-yang-awards
Visit the webpage and click to be notified when this competition opens.


Where do you submit an application?

  • Usually: Apply through your proposed supervisor's school or department, not necessarily your own. (For example, Psychology student + Biology professor = apply through Biology.)
  • Exception: Pan-McGill SURAs, only for supervisors from Anatomy & Cell Biology, Biochemistry, Pharmacology & Therapeutics, and Physiology: submit your application to the Faculty of Science.
  • Exception: Social Equity SURAs, for projects in Social Equity, Diversity and Social Justice: submit an additional copy of your application to the Faculty of Science.
  • Exception: Schull Yang International Experience Award: submit your application to the Faculty of Science.
  • For all programs: refer to websites for instruction on how to apply, deadlines, and how to “hand in” a complete application.

Important Information:


Atmospheric & Oceanic Sciences Available Supervisors and Projects: 

If you would like to work on a different project with any of the faculty members listed below, you can contact them to ask whether they are open to this.

Tips for contacting faculty members/potential supervisors/researchers are provided here: https://www.mcgill.ca/science/research/undergraduate-research/finding-opportunities.

The faculty members listed below want to supervise a project – don’t be shy! And do contact several faculty members to increase your chances of success. If you secure a potential supervisor, you and the supervisor will need to submit an application for a SURA award and/or an NSERC USRA award. (Instructions attached.) If you are eligible for both awards, apply for both in order to double your chances of receiving an award. If you do not obtain a SURA/USRA award, some supervisors may still be willing to supervise your project, either with no funding for the student, or with a small amount of funding for the student.

Prof. Frederic Fabry – frederic.fabry [at] mcgill.ca

Title: Complementarity in wind and solar energy sources between Quebec and other provinces/states.

Description: To limit carbon emissions, we must increasingly rely on renewable energy, especially wind and solar energy. And since we have limited ability to store vast amounts of energy, energy production must match as much as possible energy consumption on an hourly, daily, and monthly basis. But one of the acknowledged challenges of renewable energy is its episodic nature: winds vary, and so does solar illumination. To increase the use of renewable energy, it will be important to find sources that complement each other so another can be used when one drops out. In the Quebec province, for example, there is good potential for increasing wind energy availability, more so than for solar. But winds blow more in some months and in some time of the day. Are there other sources of energy here or elsewhere that would naturally complement, or be anti-correlated, with winds here? In this work, using reanalyses of past atmospheric data, the potential complementarity between wind energy here and solar or wind energy elsewhere will be evaluated. Renewable energy being mostly meteorologically-driven, we will also seek to explain why complementarity (or lack of) arises with other data sources here and elsewhere.

Skills: This project will require some programming ability to perform data analyses and compute statistics at different time scales. It is open to students having completed ATOC214 and ATOC215 (or equivalent).

Prof. John Gyakum – john.gyakum [at] mcgill.ca

Title: “Analysis of high-resolution temporal variability of the lower surface layer’s temperature in the Saint Lawrence River Valley”

Description: The student will conduct research to identify diurnal and seasonal variability in the vertical temperature profiles in the atmosphere’s first 10 m. The student-led research will utilize a novel dataset that consists of eight thermistors spaced logarithmically from the ground to 10 m in elevation. These thermistors are placed on seven meteorological towers located at locations ranging from near Quebec City, southwestward to Ottawa, generally throughout the Saint Lawrence River Valley (SLRV). These meteorological towers, called “Climate Sentinels,” are being deployed as part of the CFI-9 project, entitled “The Adaptable Earth Observing System.” The student will meet the project’s objectives by analyzing vertical temperature profiles in order to assess stability in the context of the larger-scale synoptic-scale dynamical structures, the diurnal cycle, and seasonality.

Dr. Gyakum may be available to supervise a student on a different project; please contact him for details.

Prof. Yi Huang – yi.huang [at] mcgill.ca

Interested in supervising one Faculty of Science student for a SURA/USRA project. Please contact Dr. Huang directly for details.

Dr. Huang has several possible projects, but is also open to projects proposed by the student.

Prof. Djordje Romanic – djordje.romanic [at] mcgill.ca

Topic: "A user-friendly MATLAB model of analytical models of thunderstorm downbursts."

Required skills: This project requires the student to have advanced MATLAB skills and proficiency in mathematics & programming.

Prof. Andreas Zuend – andreas.zuend [at] mcgill.ca

SURA/USRA project within Prof. Andreas Zuend’s group working on research in Atmospheric Aerosol Chemistry and Physics (http://www.meteo.mcgill.ca/~andreas/).

Topic: “Automating physicochemical property predictions for atmospheric aerosol modeling”

Applicant level: U1 or higher; students from Faculty of Science or Faculty of Engineering preferred.

Description: Aerosol particles are important atmospheric constituents involved in air pollution as well as in cloud droplet formation. Recent work has shown that surface properties and size effects of aerosols can be important for predictions of their ability to act as seeds for cloud formation. Typically, aerosols are multicomponent and multiphase systems involving organic and inorganic chemical species, all of which are affected by humidity and temperature changes as well as droplet surface/interface effects. Advanced versions of our thermodynamic gas–aerosol box model rely on component-specific inputs, such as pure-component surface tensions, viscosities and vapor pressures as a function of temperature. Many of these molecular properties have to be estimated for a myriad of organic aerosol constituents based on limited chemical structure information. A task that increasingly benefits from the application of cheminformatics approaches using simplified molecular-input line-entry system (SMILES) structure descriptions, customized SMARTS libraries and/or machine learning approaches. In this project, the student will work with Prof. Zuend and his group to further improve automatic property prediction tools, such as the training of an artificial neural network model for organic compound surface tension. Existing data will be combined with a search for published pure-component measurements to facilitate model training and to explore the predictability of the model as a function of the types of input quantities. Furthermore, the student will be working on a more flexible, SMILES-based user interface for our online model version of AIOMFAC.

Required/desired skills: Basic to intermediate-level knowledge of a programming language is required, ideally of modern Fortran and/or Python. Motivation and ability to learn and improve your programming skills in Fortran and Python and to work with suboptimal existing code is desired. Ability to conduct a literature search and to learn how to interpret published data sets is desired, but can be learned during the project. Some experience with JavaScript/HTML/Perl for online tools would be beneficial. Prior knowledge in basic atmospheric chemistry or meteorology is beneficial but not required for this project. During this project you will learn more about the applications of chemical thermodynamics and scientific computing in atmospheric science.

 

If you have any more AOS-specific questions, please contact Manuela Franzo at graduateinfo.aos [at] mcgill.ca.

Contact Information

Contact: 
Manuela Franzo
Email: 
graduateinfo.aos [at] mcgill.ca
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