The Faculty of Science (FSc) at York University is inviting undergraduate students to apply for the Natural Sciences and Engineering Research Council of Canada's (NSERC) Undergraduate Student Research Awards (USRA) for Summer 2025.
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.
NSERC and FSc encourage qualified Indigenous and Black students to apply for these summer research awards.
$9,632
in total value
16
weeks of funding
21
NSERC USRAs available for FSc students
3
NSERC USRAs available for self-identified Black FSc students
Information Sessions and Resources
The FSc USRA Summer 2025 Info Session and Q&A was held on Wednesday February 5.
Watch 2025 Session Recording (Zoom sign-in required)
Award Information
Projects
In progress; 2025 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: Urban Butterflies
Supervisor: Eryn McFarlane
Lab Website: https://www.yorku.ca/science/profiles/faculty/eryn-mcfarlane/
Contact Info: emcfar@yorku.ca
Project Description: Hybridization among naturally separate taxa is increasing owing to human impacts. However, there is substantial variation among outcomes at range overlaps; the two species can remain distinct, there can be a mix of rare hybrids and parental populations, or a complete breakdown of reproductive isolation. The variation in possible outcomes in replicate hybrid zones of even the same two species is not well understood. We predict that hybridization should increase with human influences, however this has rarely been tested. One possible solution is to use replicate hybrid zones to understand environmental influence on rates of hybridization, while accounting for stochastic processes.
Clouded sulphur and orange sulphur butterflies are sympatric and hybridize throughout most of the US and Canada. Colias species have high, variable rates of hybridization, are very common, and appear to vary in rates of hybridization according to the environment, this genus is an excellent system to ask how human influences affect rates of hybridization. In 2024, after sampling across parks and university campuses in Toronto, we found that the distribution of Colias colour variation is related to each the distance from roads and the number of pedestrians at a given site. We will be continuing this work this summer by 1) sampling more Colias in Toronto and 2) extracting DNA from the 2024 and 2025 Colias samples to determine how colour and urbanization related to hybridization rates.
Student Responsibilities: The USRA student will do: butterfly catching in Toronto Parks, environmental surveys in Toronto Parks, data entry of butterfly and environmental data, DNA extraction of butterflies, library prep for sequencing. Additionally, they will do informal community outreach (we get asked about butterflies often while out catching them!), as well as be an active participate in the StatsGen lab (attending and presenting at lab meetings, etc).
Desired Background/Skills: Interest in urban ecology and/or statistical genetics. Field work experience would be an asset. Lab work experience would be an asset.
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: DNA-conjugated nanoparticle sensors
Supervisor: Jennifer Chen
Lab Website: https://www.yorku.ca/science/lab/jchen/
Contact Info: jilchen@yorku.ca
Project Description:
We are interested in developing optical sensing systems for studying cellular processes, and for high-throughput screening of drug candidates, proteins and other compounds of security, biomedical and environmental importance. The chip-based sensing platforms are based on biofunctionalized plasmonic nanostructures monitored via darkfield microscopy. Our ongoing work explores protein-binding aptamers as the linkers for the nanoparticles to derive the response; major goals are to map the molecular distribution of proteins and to detect potential therapeutic small molecules that bind to the protein. Methods to enhance the detection signal, such as through amplification of the nucleic acid or proteins are investigated, concurrent with nanoparticle sensor development that focuses on identifying the factors that affect the binding efficiency (e.g. surface density of DNA, nucleic acid sequence design) and sensing merits (e.g. detection limit, sensitivity, selectivity).
Student Responsibilities:
The research spans from analytical, materials and physical chemistry to biochemistry. The student will characterize the optical properties of nanoparticles assemblies and investigate the kinetics and equilibrium properties of analyte binding. Optical techniques such as fluorescence, UV-vis and darkfield scattering-based microscopy will be employed. The student may also apply biochemical techniques such as gel-electrophoresis and biomolecular purification/isolation.
Desired Background/Skills:
Completed minimum first-year chemistry courses and ideally second-year chemistry lab (e.g. Chem 2080), or relevant 2nd-year or higher biology labs.
Students need to be motivated, committed and responsible. A successful candidate should be able to work/learn independently as well as in the team-environment.
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: 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: Dynamic Effects of Gestational Weight Gain and Maternal Health on Infant Birth Weight
Supervisor: Tianyu Guan
Lab Website: https://tianyuguan.github.io/
Contact Info: tguan@yorku.ca
Project Description: This project investigates the relationship between gestational weight gain, pre-pregnancy body mass index (BMI), and other maternal characteristics with newborn birth weight. Our objective is to understand the dynamic effects of gestational weight gain on birth weight and how maternal health and nutrition before and during pregnancy influence neonatal outcomes. We will use functional data analysis (FDA) models for prediction. We aim to develop guidelines that promote optimal pregnancy health and reduce the risks associated with low or high birth weights. In addition, we plan to create an R or Python package to make the analytical tools accessible to users beyond the statistics community.
Student Responsibilities: The selected undergraduate student will assist in data management, analysis and software package development. They will prepare data for statistical analysis, conduct literature reviews to support the project, assist in developing and applying statistical models, and contribute to the interpretation of results. They will also develop an R or Python package tailored for this statistical application. Moreover, the student will have the opportunity to co-author publications, present findings at conferences, and gain invaluable research experience.
Desired Background/Skills: The ideal candidate should have a background in statistics and data science with a strong research interest. Proficiency in statistical software such as R or Python is desirable, as is experience with data management and analysis. The student should demonstrate excellent organizational skills, attention to detail, and the ability to work independently as well as collaboratively. Prior research experience in data analysis will be considered as an advantage.
Project Title: Permutations with a given X-Descent Set
Supervisor: Mohamed Omar
Lab Website: https://www.mohamedomar.org/
Contact Info: omarmo@yorku.ca
Project Description: This project will have students investigate permutations in a symmetric group that have restricted pattern and behaviour. The purpose is to generalize similar work on what is classically known as the descent set of a permutation. This project will hinge on recent work of the supervisor. The project is a combination of combinatorics and abstract algebra.
Student Responsibilities: Students will be exploring permutation patterns using constructs from abstract algebra. They will be required to explore mathematically through computation and theoretical means. They will also be required to write results as they go along. Students will be asked to present material as well, and attend regular meetings.
Desired Background/Skills: Math 3021 (Abstract Algebra I) required; Math 4160 (Combinatorial Mathematics) suggested.
Project Title: Outputs of Low-Dimensional Quantum Channels
Supervisor: Paul Skoufranis
Lab Website: https://pskoufra.info.yorku.ca/
Contact Info: pskoufra@yorku.ca
Project Description: In upcoming work, it will be shown when there exists a quantum channel between two non-commuting n-tuples of quantum states via inequalities involving multi-valued non-commutative functions. The goal of this project is to analyze and simplify said inequalities in low-dimensional matrix algebras.
Student Responsibilities: Students will read mathematical literature, attempt to solve problems, present on their studies and progress, and meet with the professor regularly.
Desired Background/Skills: Students should have completed at least MATH 2001 and MATH 2022. Preference will be given to students that have also completed MATH 3001. In addition, MATH 4011 and 4012 would help a lot and MATH 2030, 3021, 3022, and 4021 would help some.
Project Title: Within-Host Modeling of Multi-Strain Parasite Dynamics Under Immune Response
Supervisor: Woldegebriel Assefa Woldegerima
Lab Website: https://www.yorku.ca/professor/waw/research-interests/
Contact Info: wassefaw@yorku.ca
Project Description: Understanding the interaction between parasites and the host immune system is crucial for developing effective treatment strategies. The spatial distribution of parasites and immune components within tissues plays a crucial role in immune evasion, strain competition, and infection persistence. This project integrates mathematical modeling, biological insights, and data-driven modeling to study understanding of the within-host dynamics of multiple parasite strains and strain-specific immune responses using both ordinary differential equations (ODEs) and partial differential equations (PDEs) modeling approaches.
Student Responsibilities:
- Review related literature.
- Develop a deterministic ODE model capturing the temporal evolution of parasite load, immune response activation, and pathogen-immune interactions. Extend such a model to capture multiple parasite strains and immune responses targeting distinct antigens.
- Perform Stability and Bifurcation Analysis (ODE Model): Identify conditions leading to chronic infection, parasite clearance, or immune escape; strain dominance, coexistence, or clearance.
- Use numerical simulations to explore the dynamics and immune evasio.
Desired Background/Skills:
- Have taken courses MATH2270/71 (ODEs).
- Have taken modeling course or dynamical systems course, but, it is not a MUST.
- Experience with basics on Python or R-studio or MATLAB is a plus.
Project Title: Dark Photon Production at Fixed Target Experiments
Supervisor: Nikita Blinov
Lab Website: https://nblinov.github.io/
Contact Info: nblinov@yorku.ca
Project Description: High energy proton collisions with a fixed target can be used to search for new particles. In order to interpret these experiments theoretical models are needed for the production of such hypothesized particles. In this project the student will develop a phenomenological model for the creation of a "dark photon" (one example of a hypothetical particle) in meson decays that result from proton-target collisions. The student will then compare this mechanism to other proposed production channels in this same model.
Student Responsibilities: The student will:
- Prepare a final report describing findings
- Qualitatively understand processes that can occur in proton-target collisions, and how they can result in the production of novel particles
- Develop a working knowledge of Monte Carlo tools used to simulate proton collisions
- Implement a custom Monte Carlo simulation to model meson decays into dark photons
- Meet regularly with the supervisor to discuss findings and ensure progress
Desired Background/Skills: The student will primarily develop skills in the phenomenology of particle interactions in the Standard Model and beyond; they will also develop their programming/numerical methods abilities and scientific communication skills.
Project Title: Fluid Dynamics Simulation of the young Earth’s Moon interior
Supervisor: Charles-Édouard Boukaré
Contact Info: boukare@yorku.ca
Project Description: The Earth’s Moon, due to its relatively small size, cooled rapidly and can almost be considered a geologically inactive rocky body compared to the Earth, which continues to exhibit intense internal activity. This activity is expressed on the Earth’s surface through processes such as plate tectonics and magnetic field generation. However, the Moon’s current state of relative inactivity is beneficial for planetary scientists studying the early evolution of rocky bodies. The Moon’s structure and composition have preserved a record of the dynamic processes that occurred during the first billion years of its evolution. As such, it provides invaluable constraints on the early evolution of rocky bodies and how these early processes may influence their long-term development.
The proposed research aims to shed new light on the early dynamics of the Earth’s Moon. It is part of a larger project exploring the potential link between the Moon’s early dynamics and its current surface state, which may harbor economically valuable resources.
The student will lead a campaign of fluid dynamics simulations using state-of-the-art geodynamic models developed in Professor Boukaré’s research group. These simulations will be conducted on the Niagara supercomputer of the Digital Research Alliance of Canada. Through this project, the student will have the opportunity to improve and acquire new skills in planetary science, programming, high-performance computing, fluid mechanic, geology, and chemistry. Particular emphasis will be placed on enhancing communication skills through oral presentations.
Student Responsibilities: Student’s role and responsibilities include:
- Present your result once a month in internal group meetings.
- Familiarize yourself with the broad context of the research: mantle convection, planetary sciences, computational fluid dynamics.
- Familiarize yourself with access to the Supercomputers of Digital research Alliance Canada: bash scripting, workload manager system (SLURM) and SSH access.
- Familiarize yourself with the input file of the code. The parameters that will be explored in the simulations campaign are located in this file.
- Run a first batch of simulations, download the results, and produce human-readable plots.
- Discuss the results with the supervisor and identify the next simulations that should be run, i.e., the parameters that must be explored in a systematic fashion.
Desired Background/Skills: Intellectual curiosity, motivation, and a strong interest in one of the following disciplines are crucial: programming, high-performance computing, and planetary sciences.
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: Neutrino Interaction Studies with MINERvA Data for DUNE
Supervisor: Deborah Harris
Contact Info: deborahh@yorku.ca
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).
Project Title: Electric dipole moment of the electron
Supervisor: Eric Hessels
Contact Info: hessels@yorku.ca
Project Description: We are beginning a new project to measure the electric dipole moment of the electron. The measurement uses a new technique which we refer to as EDM cubed (Electric Dipole Measurements using Molecules in a Matrix). The EDM cubed method has the potential to improve the measurement accuracy of the electric dipole moment of the electron by several orders of magnitude. The Standard Model (SM) predicts a very small value for the electron electric dipole moment. Extensions to the SM are needed to deal with the SM's failure to predict both the asymmetry between matter and antimatter in the universe and the presence of Dark Matter. These extensions also predict a much larger value for the electron electric dipole moment, and therefore the EDM cubed measurements will provide direct tests for the theories of antimatter and Dark Matter. Because of the extreme accuracy of the EDM cubed measurements, they will be sensitive to physics at energies higher than that which can be probed at the CERN large hadron collider. The measurement will use barium monofluoride molecules embedded in a solid argon matrix. The first steps of this research will be to assemble the vacuum system and cryogenic system needed to freeze argon. An ion beam will produce the barium monofluoride positive ions, and this beam will be resonantly neutralized by grazing collisions with a single-crystal tungsten surface. The resulting neutral molecules will be combined with a flow of argon to embed it into the argon solid. Exciting these molecules with green light will lead to fluorescence which will be analysed with a grating monochromator to assess the shifts caused by the matrix.
Student Responsibilities: This research involves modelling, design, building, testing, data collection and analysis. The experiment involves vacuum equipment, lasers, optics, microwave equipment and test and measurement equipment. The student will work with a team that includes three undergraduate students, four graduate students, one postdoctoral fellow and the P.I. to embed BaF molecules into an Ar matrix and to study the spectrum of these molecules.
Desired Background/Skills: Physics Undergraduate Courses and Laboratories.
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: Experimental Particle Physics Search with the ATLAS Experiment
Supervisor: Wendy Taylor
Lab Website: https://wendytaylor.info.yorku.ca/
Contact Info: taylorw@yorku.ca
Project Description: The student will perform experimental particle physics research as a member of the international ATLAS Experiment, which operates at the CERN Large Hadron Collider (LHC) in Geneva, Switzerland. As a member of the York ATLAS group, the student will support the search for a hypothetical particle known as the magnetic monopoles. This will primarily involve computational studies of simulated or real data.
Student Responsibilities: The student will be provided with prepared n-tuples containing kinematic properties of simulated and possibly real proton-proton collision data. Magnetic monopole particles will be represented in the simulated data samples. The student will perform the computational studies within the Linux operating system. The student will develop Python code to interface with the particle physics analysis tool, ROOT, to make graphs from the n-tuples. The student will develop and optimize algorithms for preferentially selecting magnetic monopoles. The student will evaluate the performance of the search algorithm and investigate any unexpected behaviour or results.
Desired Background/Skills:
- Successful completion of third-year physics courses PHYS 3020, 3040 and 3220.
- Computational experience and Python programming skills, including successful completion of EECS 1541 or equivalent and PHYS 2030.
- Some experience with Mac OS or Linux would be an asset.
- Some knowledge of particle physics would be an asset.
Project Title: Dissipational dark matter and the origin of supermassive black holes
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. This research will employ computational simulations to investigate the potential role of such forces in shaping cosmic structure. Specifically, it will model dissipative dark matter interactions that could lead to the formation of compact objects, including black holes, in the early Universe. These mechanisms may provide a viable explanation for the enigmatic origins of supermassive black holes observed at the centers of galaxies.
Student Responsibilities: The student will collaborate with an international research team to conduct analytical and computational work, contributing to novel dark matter simulations incorporating dissipative interactions. Their tasks will include: (1) applying quantum mechanical partial wave scattering theory to calculate rates for both dissipative and elastic dark matter collisions, (2) integrating these scattering results into an existing Python-based gravothermal fluid dynamics code for dark matter simulations, and (3) executing large-scale simulations on the Canadian supercomputer cluster Niagara. Additionally, the student will review relevant scientific literature, gaining both a broad understanding of dark matter physics and a deeper insight into dissipative dark matter interactions.
Desired Background/Skills: Completion of PHYS 2030 or equivalent familiarity in Python.
If you are a supervisor and would like to add a project, please complete this form for submission.
