The Faculty of Science (FSc) at York University is inviting undergraduate students to apply for the Natural Sciences and Engineering Research Council's (NSERC) Undergraduate Student Research Awards (USRAs) for Summer 2026.
NSERC USRAs are meant to nurture your interest and fully develop your potential for a research career in the Natural Sciences and Engineering (NSE) disciplines. They are also meant to encourage you to undertake graduate studies in these fields by providing research work experience that complements your studies in an academic setting. For Summer 2026, FSc has been allotted 20 NSERC USRAs + 2 NSERC USRAS for self-identified Black students.
In addition to the NSERC USRAs, FSc will be providing 12 awards known as the Earle Nestmann Undergraduate Research Awards (ENURAs). These have been made possible in part through a generous donation from FSc Alumnus, Earle Nestmann and FSc.
Note that for the first time this year, FSc will also be offering 2 Undergraduate Research Awards for International students only. These are sponsored jointly through a contribution from co-educational institution, Ace Acumen Heights and an FSc supervisor. These are called the Ace Acumen Heights Research Scholarships. To apply for these scholarships, you must be an FSc International student who has obtained the agreement of their prospective supervisor indicating that the supervisor is able and willing to make the required matching $6,000 contribution. Applicants must note on the FSc Machform that they are specifically applying for the Ace Acumen Heights Research Scholarship with the expressed agreement and permission of their prospective supervisor.
NSERC and FSc encourage qualified Indigenous and Black students to apply for all of the above summer research awards.
NSERC USRAs
16
weeks of funding
20
NSERC USRAs available for FSc students
2
Additional NSERC USRAs available for self-identified Black FSc students
$9,856
in total value - $6,000 paid by NSERC, $3,856 paid by FSc supervisor
ENURAs
16
weeks of funding
12
ENURAs available for FSc students
$9,856
in total value - $6,000 paid by Earle Nestmann, $3,856 paid by FSc supervisor
Ace Acumen Heights Research Scholarships
16
weeks of funding
2
scholarships available for FSc International students
$12,000
in total value - $6,000 paid by Ace Acumen Heights, $6,000 paid by FSc supervisor
Information Sessions and Resources
The FSc USRA Summer 2026 Info Session and Q&A was hosted by FSc Research Services and held on zoom on Wednesday January 28, 2026 from 1:00 p.m. - 2:30 p.m.
View 2026 Info Session Slides | Watch 2026 Session Recording (Zoom sign-in required)
Award Information
Projects
In progress; 2026 projects will be added on an incoming basis.
PLEASE NOTE: These are just some of the projects that are available. It is recommended that as a student, you be proactive in reaching out directly supervisors that you are interested in working with as soon as possible to see if they are accepting USRA students. In order to apply, you must have agreed with a potential supervisor on a proposed project.
Project Title: Conserved regulation of divergent plant metabolic defenses
Supervisor: Nik Kovinich
Lab Website: https://www.kovinichlab.com/
Contact Info: kovinich@yorku.ca
Project Description: Plants biosynthesize defense metabolites (i.e. phytoalexins) in response to pathogen attack. These metabolites, are diverse in chemical structure and biosynthetic origin among plant species and include the phenylalanine-derived glyceollins from soybean, the phenylpropanoid-derived stilbenes from grapevine, and the tyrosine-derived camalexins from the model plant Arabidopsis. All of these phytoalexins have unconventional anticancer activities that render them desirable for pharmaceutical development. Plants are the most economical source of many phytoalexins but biosynthesize them only transiently and in low amounts, limiting their commercial accessibility.
Despite that phytoalexins are biosynthesized from diverse biosynthetic pathways in different plant lineages, we have discovered that their biosynthesis is regulated by a conserved group of transcription factors. Now we aim to understand the mechanism, first by testing whether the conserved transcription factors directly bind and regulate the cis-acting elements of lineage-specific phytoalexin biosynthetic genes.
We currently have funding from an NSERC Discovery Grant for this USRA position.
Student Responsibilities: The student's role will be to identify gene targets of the transcription factors by conducting promoter-luciferase reporter assays and by assisting with chromatin-immunoprecipitation quantitative polymerase chain reaction (ChIP-qPCR).
Desired Background/Skills: The student will learn how to present scientific information through mentoring and by participating in weekly lab meetings. (S)he will receive one-on-one lab training from NSERC PGS-D student Ivan Monsalvo and from the Principle Investigator.
Project Title: Characterizing hormonal regulators and their signaling cascades in insect excretory organs
Supervisor: Jean-Paul Paluzzi
Lab Website: https://paluzzi.lab.yorku.ca/
Contact Info: paluzzi@yorku.ca
Project Description: Neuropeptides and their receptors play a central role in the regulation of most physiological processes in animals. Research in my laboratory is mainly focused on investigating the function of neuropeptides and their receptors in insects. To understand the role and importance of distinct neuropeptide systems, we combine in vitro, in vivo and heterologous high-throughput techniques. Recent evidence of successful implementation of these methods includes our studies on CAPA peptides, which we found activate their cognate receptor forming an essential anti-diuretic regulatory system in mosquitoes (Sajadi et al., 2018 J. Exp. Biol; Sajadi et al., 2020 Sci. Reports). Our latest advances in this area link anti-diuretic hormone control of the renal organs to inhibition of the V-type ATPase (known also as the proton pump), which drives secondary active transport along with osmotically obliged water (Sajadi et al., 2023 PNAS). This current project expands upon related hormones and their signaling cascades using a model organism, namely the fruit fly, Drosophila melanogaster. With the powerful genetic tools available, this study in the fly will examine the signaling cascade linking hormonal control of the renal organs. Specifically, given that most diuretic and anti-diuretic hormones signal via G protein-coupled receptors, we will use reverse genetics to identify downstream targets including a soluble guanylate cyclase (the enzyme responsible to increasing cGMP levels) and protein kinase G (kinase dependent upon cGMP) that are both critical for inhibition of the renal organs. This NSERC USRA project will include molecular, genetic, behavioural and physiological investigations of the above-mentioned and other regulators of the excretory system in insects.
Student Responsibilities: Student will help characterize key components involved in anti-diuretic hormone control of the insect renal organs. Student will rear insects for research by maintaining fly stocks, setting up crosses for experiments including reverse genetic screens, conduct physiological and behavioural bioassays to validate the role of critical enzymes and signaling molecules in control of the insect excretory system. Finally, student will collect and analyze data and present results during weekly meetings.
Desired Background/Skills: Currently enrolled in or previously completed animal physiology, genetics and molecular biology (or equivalent) courses with grades of >80% is preferred. Students with previous laboratory experience (practicum, RAY or other opportunity) is a bonus.
Project Title: Protein Motions in Cancer and Neurodegenerative Disease
Supervisor: Derek Wilson
Lab Website: http://yorku.ca/dkwilson
Contact Info: dkwilson@yorku.ca
Project Description:
Our lab uses home-build devices combined with cutting edge bioanalytical mass spectrometry platforms to study the rapid - and sometimes dangerous - motions undergo as they carry out their biological roles (or go rogue and cause disease) in the cell. Our undergraduate projects will have you working with Tau protein - one of the two proteins that misfolds and clumps together in Alzheimer's disease - studying how phosphorylation by different enzymes causes it to shift it's 'conformational bias' from the 'safe' form you have in your brain right now to the 'dangerous' form that starts 'clumping' and neurodegeneration.
Student Responsibilities:
Students will: Learn to express and purify Tau protein; Learn to characterize Tau using 'native' mass spectrometry; Learn to conduct millisecond H/D exchange experiments to explore Tau conformational dynamics; Learn to phosphorylate Tau; Present their work at group meetings and conferences; Write up any novel / impactful findings!
Desired Background/Skills:
You'll need: To be an independent learner/thinker, ready to (eventually) work independently in the lab and read relevant background papers on your own; To be able to work as part of a team; To be ready to make the best of the opportunities working on a real-world, high level research project affords you! Some skills in biochemistry lab would be nice, but the ability to learn hands-on skills quickly and effectively is more important than pre-existing knowledge! Some knowledge of molecular-level biochemistry / structural biology would be nice, but the ability to quickly and holistically learn the biological background is more important!
Project Title: Characterizing intramolecular interactions in molecules of astrochemical or atmospheric interest
Supervisor: Jennifer van Wijngaarden
Lab Website: https://www.yorku.ca/vanwijng/
Contact Info: vanwijng@yorku.ca
Number of positions: 1
Project Description:
The conformer geometries and relative energy ordering of ethers and thioethers changes depending on the identity of the chalcogen bridge atom (O versus S) and the nature of the organic side chains. These geometric preferences reveal a great deal about the underlying intramolecular interactions that stabilize the molecular shapes. Fourier transform microwave (FTMW) spectroscopy is an excellent tool for probing mixtures of conformers as the molecules are probed in a solvent-free environment allowing bond lengths and angles to be extracted with great precision. In particular, this project will build on recent progress the group has made in studying such compounds to now explore the role of chalcogen atom in directing the positioning of amine or epoxide groups. This project will involve the measurement and analysis of the rotational spectra of these compounds and their minor isotopologues using two state-of-the-art spectrometers at York University. The experimental results will be complemented with a computational study involving molecular dynamics and quantum chemical calculations to identify potential stable forms and their relative energies. The goal of the analysis is to derive accurate experimental geometries for each observed conformer and to use the computed electronic structure to rationalize the underlying reasons for stability. This project will extend our current knowledge of the forces that govern the potential energy landscape of organic ether and thioethers.
Student responsibilities:
The student will learn to use computational tools from Compute Canada to predict conformer structures and energies as well as their corresponding patterns of rotational transitions before using custom spectrometers to collect the experimental spectrum for comparison. Once the spectrum is collected (over several weeks), it will be fit and analyzed. Through this project, the student will be trained to use modern spectrometers (vacuum system, gas mixtures, electronics) and software and will gain an in-depth understanding of the underlying theory of rotational spectroscopy and its connection to molecular geometry.
Desired background/skills:
To get the most of this experience, the student should have successfully completed a course in quantum mechanics such as CHEM3010 or the PHYS equivalent.
Project Title: Efficiency of Bonus-Malus-System for Experience Rating
Supervisor: Jingyi Cao
Contact Info: jingyic@yorku.ca
Project Description: The Bonus-Malus System (BMS) is a mechanism used by insurance companies to adjust premiums based on an insured individual's claim history. Policyholders incur surcharges (maluses) if they file one or more claims, while they receive discounts (bonuses) if they remain claim-free.
This project evaluates the efficiency of the BMS from two perspectives:
- Adaptation to Risk Profile Changes – Examining whether the BMS fairly adjusts premiums in proportion to the actual risk each policyholder represents. The student will assess fairness using Loimaranta efficiency and De Pril efficiency.
- Optimal Policyholder Retention – Addressing the ex-ante moral hazard in rating systems, where policyholders may strategically decide whether to report small claims to avoid future premium increases. Recent studies by Cao, Li, Young, and Zou (2023, 2024) have analyzed optimal reporting strategies for both full and deductible insurance. The student will apply the classical Lemaire algorithm to determine the optimal retention level and explore potential extensions of these reporting strategies.
Student Responsibilities:
- Review the provided readings to gain an understanding of the modelling of the BMS.
- Apply the Loimoranta efficiency and De Pril efficiency calculations to analyze a given BMS.
- Conduct a literature review on the phenomenon of bonus hunger and reporting strategy, exploring both empirical evidence and theoretical framework.
- Implement the Lemaire algorithm to determine the optimal retention level.
- Investigate extensions of BMS that incorporate claim sizes.
Desired Background/Skills: Students should have completed MATH 2030, 2131, 2280. Preference will be given to students that have also completed MATH 4280 and MATH 4430.
Project Title: Social Homophily, Behavioural Dynamics, and Infectious Disease Transmission
Supervisor: Seyed Moghadas
Lab Website: https://www.yorku.ca/science/research/abm-lab/
Contact Info: moghadas@yorku.ca
Number of positions: 1 to 2
Project Description: Human behaviour plays a critical role in shaping the spread of communicable diseases. Beyond biological factors, patterns of social interaction such as who interacts with whom, and how individuals influence one another’s beliefs can substantially alter epidemic outcomes. This project focuses on the role of homophily (i.e., the tendency of individuals to preferentially interact with others who share similar attitudes or behaviours, and how such social clustering affects disease transmission and control. The student(s) will work on a mathematical and computational modelling project that extends classical epidemic models to incorporate attitude-driven contact patterns and behavioural change. The population is divided into groups based on vaccination attitudes, and disease transmission occurs through physical contacts structured by homophily. In addition, the model allows for attitude change through social influence, including both physical interactions and virtual exposure (e.g., social media). The project will explore how these interacting processes can lead to non-intuitive outcomes, such as large outbreaks occurring despite high overall vaccination coverage, or abrupt shifts in epidemic risk driven by social polarization. The student will contribute to developing and analyzing a system of differential equation models, implementing simulations and fitting to social data collected during the COVID-19 pandemic, and exploring how epidemic outcomes depend on key parameters such as the strength of homophily, contact rates, and persuasion probabilities. Emphasis will be placed on understanding mechanisms, not just producing simulations: why certain social structures amplify risk, how clustering redistributes infections across groups, and when simplifying assumptions (such as random mixing) break down. Expected outcomes include: (i) A working computational implementation of a homophily-based epidemic model; (ii) Quantitative results showing how social structure affects outbreak size and infection risk; (iii) Visualizations suitable for academic presentations and reports; (iv) A short written summary of findings, potentially contributing to a future manuscript or Summer Undergraduate Research Conference presentation. The project provides training at the interface of mathematics, data science, and public health, and is well suited for students interested in applied mathematics, epidemiology, computational modelling, or complex systems.
Student responsibilities: The undergraduate student(s) will work within a collaborative environment at the ABM-Lab to support ongoing research on behavioural and social drivers of infectious disease transmission. Specific responsibilities will include: (i) Learning and understanding compartmental epidemic models (e.g., SIR-type models) and their extensions to include behavioural and social processes; (ii) Assisting in the formulation and interpretation of models that incorporate homophily and attitude change; (iii) Implementing and modifying simulation code (e.g., using MATLAB, Julia, or Python) to explore model behaviour under different parameter settings; (iv) Fitting data and running numerical experiments to assess the impact of social clustering, vaccination attitudes, and behavioural feedback on epidemic outcomes; (v) Producing clear figures and plots that summarize simulation results and illustrate key mechanisms; (vi) Participating in regular weekly meetings at the ABM-Lab to discuss progress, challenges, and interpretation of results; and (vii) Maintaining organized code, documentation, and notes to ensure reproducibility. The student(s) will be encouraged to think critically about modelling assumptions, ask questions about interpretation, and contribute ideas for extensions or alternative scenarios. Depending on progress and interest, the student(s) may also assist with drafting short summaries of results or preparing materials for journal publications. The emphasis throughout will be on skill development, conceptual understanding, and exposure to real-world research problems.
Desired background/skills: Applicants should be undergraduate students enrolled in FSc programs (e.g., Applied, Mathematics, Statistics, Data Science) having strong interest in mathematical modelling or computational approaches to real-world problems. Desired background and skills include: (i) knowledge of differential equations or dynamical systems; (ii) Some experience with programming (e.g., MATLAB, Julia, Python, R, or similar); (iii) Comfort working with equations, simulations, and data analysis/visualization; and (iv) Willingness to learn new concepts in epidemiology and social dynamics. Prior experience with epidemic models, network theory, or agent-based modelling is an asset but not required. Strong analytical thinking, curiosity, and the ability to work independently with guidance are more important than specific technical expertise.
Project Title: Euclidean Ramsey Theory
Supervisor: Mohamed Omar
Contact Info: omarmo@yorku.ca
Project Description: Euclidean Ramsey Theory is a branch of extremal combinatorics that asks extremal questions about forced geometric configurations in prescribed point sets in Euclidean spaces. This project aims to use state-of-the-art techniques in extremal combinatorics, particularly the slice-rank and partition-rank polynomial methods, to improve state-of-the-art bounds in the area.
Student Responsibilities:
- A thorough literature review of recent techniques using slice-rank and partition-rank methods in Euclidean Ramsey Theory;
- Using software to test the viability of these methods on various problems in the research field;
- A thorough journal documenting the research process, written in latex
- A draft of an article with all findings from the summer
Desired Background/Skills: Student should have taken Algebra I and Algebra II. At least one of Graph Theory or Combinatorics is recommended.
Project Title: Precision Metrology with Homebuilt Laser Systems
Supervisor: Ananthraman Kumarakrishnan
Lab Website: http://datamac.phys.yorku.ca
Contact Info: akumar@yorku.ca
Project Description:
My group has developed a new class of low cost, homebuilt, vacuum-sealed, auto- locking laser systems that can be frequency stabilized with respect to atomic, molecular, and temperature tunable solid state frequency markers without human intervention.
Summer research projects will focus on the applications of these laser systems in several exciting experiments that include:
- Ultra cold atom sensors that measure gravitational acceleration with high precision
- Optical lattices that can realize the most accurate measurement of a diffusion coefficient-a parameter that is required to model the performance of the most sensitive magnetometers
- Coherent transient experiments that are capable of realizing the most precise measurements of atomic lifetimes
- Free space optical tweezers that trap dielectric particles, and rapidly determine their masses by investigating kinematics on fast time scales
Student Responsibilities:
Development of individual research projects, assistance to graduate students
Desired Background/Skills:
Aptitude for experimental physics, willingness to take on challenging problems, hands on skills, computer interfacing.
Project Title: Analysis of exceptional quasar outflows
Supervisor: Patrick Hall
Lab Website: phall@yorku.ca
Contact Info: https://www.yorku.ca/phall/HOME/astro.html
Project Description:
Quasars are disks of matter around supermassive black holes in galaxy cores which host inflows through the disk and outflows above and below the disk. My research group has access to a large database of spectroscopy and photometry of quasars from the Sloan Digital Sky Survey. We have found quasars with exceptional emission and absorption properties related to outflows of matter from the quasars. We are modelling those properties to compare to the predictions of models of disks and their outflows. The specific quasar(s) to be studied in the project will be determined during the application project.
Student Responsibilities:
The student will learn about quasars through textbooks and lectures both online and in person. The student will work with Prof. Hall and his group on scientific programming for astronomy data analysis using python, MATLAB, etc., and is expected to contribute significantly to analyzing spectra and photometry and to writing up scientific results for publication in a peer-reviewed journal.
Desired Background/Skills:
High marks in all courses, especially in astronomy courses and in computational courses involving python (at minimum EECS 1541 or equivalent, and preferably PHYS 2030 or equivalent).
Project Title: Biophotonics measurements and modulation of living system
Supervisor: Ozzy Mermut
Lab Website: https://omermut.lab.yorku.ca/
Contact Info: omermut@yorku.ca
Project Description: How do we manipulate bioluminescence? Pyrocystis fusiformis is bioluminescent alga found in coastal waters. The species is known for emitting a beautiful blue light when mechanically disturbed by its water environment and predators. This bioluminescence is produced by a chemical reaction involving luciferin-luciferase catalysis within scintillon organelles in the cell’s cytoplasm. This reaction is triggered by mechanical stress on the cell, however, the complete signaling mechanism is not well understood. What if we can control these organism’s bioluminescence behaviour with light stimulus? Thus, the goal of this project is to study the time-resolved bioluminescence behavior under different stimulator conditions with our novel fast an ultra-sensitive home-built photon-counting device. Ultimately, we aim to incorporate molecular optical photoswitches to photonically biomodulate the photosynthetic and bioluminescent behaviour of these fascinating single cell organisms.
Student Responsibilities: In this highly trans-disciplinary project, conducted collaboration with Chemistry and Physics collaborators, the biophysicist will learn development of biophotonics single photon counting setup to measure bioluminescence kinetics. The student will prepare and integrate optical photo-switching chromophores (azobenzenes) into the dinoflagellates and conduct biomodulation experiments with pump-probe spectroscopy, determining the energetic and kinetic properties.
Desired Background/Skills: The received training will be in biophysics, physics, photonics, and molecular time-domain spectroscopy instrumentation in a highly interdisciplinary team of physicists, chemists, computational scientists, and opto-electronic engineers. The student is expected to present at group meetings throughout the project for training and development of scientific communication skills. Students will be supported by the supervisor through weekly meetings.
Project Title: Studying Fast Radio Bursts with CHIME
Supervisor: Paul Scholz
Contact Info: pscholz@yorku.ca
Project Description: The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a revolutionary radio telescope, located in British Columbia. In its first five years of operation, CHIME has discovered hundreds of new Fast Radio Bursts (FRBs), and this discovery rate is expected to keep course if not further increase. FRBs are millisecond-long pulses of radio waves from far outside of our Galaxy of unknown origin. CHIME has brought about a new landscape in the FRB field; for the first time we are able to study FRB as a population. There are several potential projects using CHIME/FRB data including software and signal processing pipelines, data analysis and visualization. The student will have opportunities to develop skills in radio signal processing, Python programming, statistics, simulations, and machine learning.
Student Responsibilities: The student will work with Prof. Scholz and the wider CHIME/FRB team analyzing CHIME/FRB data and helping to develop/improve CHIME/FRB software pipelines using Python. Students will work in a collaborative and vibrant research environment through interactions with CHIME/FRB members at several other institutions. The student will give presentations and share results with the team.
Desired Background/Skills: Interest in astrophysics. Experience with programming, particularly in Python.
Project Title: Production of new dark forces at particle accelerators
Supervisor: Sean Tulin
Contact Info: stulin@yorku.ca
Project Description: Dark matter constitutes the most abundant form of matter in the Universe, shaping the evolution of cosmic structures through its gravitational influence. However, its fundamental nature remains elusive, as it cannot be explained within the current framework of fundamental physics. A key open question is whether dark matter interacts solely via gravity or if it experiences additional fundamental forces, analogous to electromagnetism and the nuclear interactions of ordinary matter. If dark matter possesses new fundamental forces, dark force bosons may be discovered in particle accelerator facilities, opening a window toward exploring dark matter physics in the laboratory.
Student Responsibilities: This research will employ theoretical modeling, data analysis, and numerical simulations to predict experimental signatures of novel dark force bosons. Student tasks will include: (1) learning particle physics models of dark matter and dark forces, (2) performing numerical fits to experimental data to determine key inputs needed to calculate the dark force production rate, and (3) performing numerical Monte Carlo simulations to model experimental signatures and detection rates for new physics signals at accelerator facilities.
Desired Background/Skills: Completion of PHYS 2030 or equivalent familiarity in Python.
Project Title: Studying Neutrino Interactions
Supervisor: Deborah Harris
Contact Info: deborahh@yorku.ca
Lab Web Site: https://www.yorku.ca/professor/deborahharris/
Number of positions: 1
Project Description: This job will involve analysis of data that was recorded by the MINERvA detector which operated at Fermi National Accelerator Laboratory in Batavia, Illinois. The MINERvA experiment is designed to study the interactions of neutrinos in a variety of different nuclei in order to understand those interactions and how the nuclear environment modifies the particles that emerge from those interactions. This understanding is critical for neutrino experiments like DUNE and T2K, which measure the probability of neutrinos changing from one kind to another over time. Those measurements require experiments to simulate how neutrino energy is translated into energy that can be measured in a detector, since "time" for a particle changes depending on that particle's energy (known as "time dilation" in special relativity).
Student responsibilities: Part of the work will involve developing new analysis code to extract measurements of the probability that neutrinos interact as a function of the momentum of the outgoing particles from the interaction. Since neutrinos are neutral they leave no trace in the detector until they interact with a nucleus (or electron) in the detector to create or boost charged particles which then leave signals as they cross different detector elements. Another part of this job involves contributing to the efforts of the collaboration to run simulations of the experiment which allow uncertainties on the measurements to be evaluated. Those simulations are often more CPU time-consuming than analyzing data because the experiment relies on simulations that are many times the statistics of the data samples. The job will also involve preparing or improving documentation on how to use the collaboration's computing infrasturcture, and possibly documentation for undergraduates on how the MINERvA detector and associated neutrino beamline works.
Desired background/skills: The successful applicant will be able to program in C++, Python, and ROOT (or be willing to develop their skills with online tutorials), and will be able to work effectively in a linux environment. The job will involve using the software infrastructure that is being written by the collaboration, and contributing to that infrastructure. The successful applicant will be able to work independently, and to present their results clearly at occasional meetings with the MINERvA and DUNE Collaborations. Since many presentations will have to be through zoom, the successful applicant will also have access to reasonably good internet to allow effective communication through online platforms (mostly by being on the York campus but some amount of remote work is also an option depending on the independence and coding skill of the successful applicant).