To find out how to apply for USRAs, visit the department's Undergraduate Summer Research Awards page.

2025 Summer project descriptions will be updated as projects are submitted. Please see previous years' projects for more information about PHAS Faculty projects.

*Students: This will be a continuously growing list. Faculty members who are not listed here might be interested in supervising USRA students; please contact them directly (listed here or not) if they are engaged in research that interests you.
 

1.CHIME telescope: options for Pulsar and/or FRB projects

Contact: Ingrid Stairs | Email: stairs@astro.ubc.ca

This summer project will entail Pulsar and/or FRB work with the CHIME telescope: in particular, looking at slow pulsars to measure diffractive scintillation properties as a function of frequency; CHIME's wide fractional bandwidth could allow new probes of the predicted scaling of this phenomenon. Also, this project can include an investigation of wideband profile changes in these pulsars and comparison to narrowband literature measurements and conclusions. FRB projects could involve, for example, interference-excision improvements and testing.

For more information about the CHIME telescope, see here.
 

2. Scanning Tunnelling Microscopy in the Laboratory for Atomic Imaging Research

18. One-upping mother nature with synthetic quantum minerals
Contact: Alannah Hallas and Austin Ferrenti | Emails: alannah.hallas@ubc.ca and austin.ferrenti@ubc.ca 

In the development of new magnetic materials, we’re usually limited by the types of crystal structures stabilized in the lab by conventional synthesis methods. However, natural geologic processes often produce minerals with more exotic arrangements of magnetic cations. Exploring synthesis methods that mimic these processes offers the potential to grow our own, entirely new magnetic versions of natural minerals. The student working on this project will join the Hallas group and work in our state-of-the-art crystal growth laboratories at Blusson QMI. Their research project will involve learning hydrothermal and hydroflux crystal growth techniques, toward the stabilization of new magnetic materials based on the natural minerals zemannite and corkite. 
No prior knowledge or experience is required, but an interest and prior coursework in chemistry, physics, and/or geology is an asset.

19. Earth-Space Sustainability
Contact: Aaron Boley | Email: acboley@phas.ubc.ca 

Humanity’s rapid and accelerating expansion into space benefits society, opens pathways to scientific discoveries, and advances economic opportunities. Satellites already play vital roles in weather forecasting, food production, forest fire detection, climate science, communications, navigation, search and rescue, disaster relief, military operations, and arms control verification. There are also negative consequences, from the loss of dark and radio-quiet skies, to space debris and collision risks on orbit, casualty risks from reentering rocket bodies and satellites, and changes to the atmosphere from both launches and reentries.
These negative consequences arise because space is generally not regarded as an environment in need of protecting, nor is it seen as being closely connected to Earth’s environment. In reality, the two are so closely related that we need to speak of the Earth-Space system. Adding to the challenges, the expansion into space is driven by a handful of powerful states and large private companies who see themselves competing for national, economic, and military advantage in an “area beyond national jurisdiction” that is largely devoid of clear, widely agreed, enforceable rules. Yet the negative consequences of their actions are borne by everyone on Earth, including succeeding generations.  

Positions are available under this theme that would explore one or more of the following:
* Calculations of orbital carrying capacities
* Observations of satellites and debris
* Upper atmosphere impacts arising from spacecraft launch and reentries
* Disarmament and space weapons

Contact: Sabrina Leslie | Email: sabrina.leslie@msl.ubc.ca | Web: https://leslielab.msl.ubc.ca/

Nanoparticles are increasingly used in pharmaceutical applications. This research project will use single-particle confinement microscopy to investigate the biophysical properties, stoichiometry and kinetics of nanoparticle assemblies and their interactions. This technique entraps particles in femto-liter reaction wells and allows prolonged monitoring of reactions. It also enables direct visualization of interactions between chemical species and nanoparticles.

For this project, the student will perform single-particle experiments to investigate and quantify probe nanoparticle interactions as well as being part of developing image analysis tools to extract detailed particle information from the microscopy videos. For example, particle tracking algorithms can be used to extract valuable information such as diffusion coefficients and fusion kinetics. Moreover, by using deep learning image analysis it is possible to improve the characterization of nanoparticles with weak signal. This project is best suited for engineering physics students with an interest in computer science and biology since we will be applying physical tools to understand out data.

The student will receive training in quantitative image analysis as well as hands-on microscopy and will work closely with a research fellow and graduate student. Weekly meetings with the supervisor and collaborators, and daily interactions with members of our interdisciplinary research group including the nanomedicine network, will support and guide the project. In addition to gaining hands-on research experience, anticipated outcomes of this summer research project include virtual presentations with lab members, providing key training in writing and oral communication.

21. Single-molecule imaging of DNA-DNA interactions within live Escherichia coli cells.
Contact: Sabrina Leslie | Email: leslielab@msl.ubc.ca | Web: https://leslielab.msl.ubc.ca/

DNA, as a long, double-stranded polymer, can form a variety of secondary structures at sequence specific locations. Such structures have important impacts on cellular function. For example, single-stranded regions within DNA can serve as binding sites for proteins and play a role in regulating gene transcription. Previous work in the Leslie Lab has investigated sites susceptible to forming single-stranded regions when the DNA is supercoiled (over- or under-twisted). These studies investigated how environmental factors, such as temperature, salt and macromolecular crowders, affected the denaturation of these regions, to better understand the biophysics underpinning these transitions. However, the environment within a cell is complicated, and to fully understand how environment impacts secondary structure formation, these in vitro results should be complemented with in vivo measurements.

In this project, the student will build upon our in vitro assays to study structural transitions within DNA plasmids in live E. coli cells. They will test methods to introduce a fluorescent oligonucleotide probe into the cells without killing the cells. They will then use state-of-the-art confocal imaging to follow the probes within the cells and image them binding to target structures within DNA plasmids. Finally, they will compare the probe binding in vivo to our results obtained in vitro.

The student will receive hands-on training and guidance from the Leslie Biophysics Research Group, including day-to-day guidance from graduate students and postdoctoral fellows in the lab, regular meetings with the research team and principal investigator, and interactions with the surrounding interdisciplinary environment at the Michael Smith Labs. Through the course of the summer, the student will hone their oral communication skills through opportunities to present at group meetings and interact at local events such as the Michael Smith Labs Summer Poster Fair. 
 

22. Implementation of deep learning algorithms to improve detection of probe-plasmid interactions within single-molecule Convex Lens-induced Confinement microscopy videos
Contact: Sabrina Leslie | Email: leslielab@msl.ubc.ca | Web: https://leslielab.msl.ubc.ca/

DNA is a long polymer molecule and when it is supercoiled (over- or under-twisted), secondary structures can form in the DNA at predictable, sequence specific locations. To study the formation of these structures, the Leslie Lab has developed an assay where small fluorescently-labelled probes are mixed with plasmids containing the sequence of interest, such that the probe will bind to the plasmid only if the structure is present. The probe-plasmid solution is then imaged with Convex Lens-induced Confinement (CLiC) microscopy, where small volumes of the solution are trapped in microwells and the number of probes bound to plasmids is identified. However, background fluorescence within the microwells, the low signal produced by diffusing single-fluorophores, and the fast photobleaching of these fluorophores provide difficulties in developing an algorithm to automatically detect the number of probes bound to plasmids in a given video. Recent advances in machine learning provide a wide array of tools that can help address these issues and improve the robustness of image analysis of single-molecule videos, increasing the throughput of analysis.

In this project, the student will test and implement deep learning models to automate the detection of probes bound to plasmids in CLiC microscopy videos. They will first identify, train and test a variety of existing models on simulated videos. Once they identify and train a suitable model, they will test it on a range of real data, where the signal, noise, and background signal varies. Finally, once a model is developed that attains a suitable accuracy, they will incorporate the model into the existing analysis pipeline.

The student will receive hands-on training and guidance from the Leslie Biophysics Research Group, including day-to-day guidance from graduate students and postdoctoral fellows in the lab, regular meetings with the research team and principal investigator, and interactions with the surrounding interdisciplinary environment at the Michael Smith Labs. Through the course of the summer, the student will hone their oral communication skills through opportunities to present at group meetings and interact at local events such as the Michael Smith Labs Summer Poster Fair. 

23. Exoplanet and Solar System Science 
Contact: Michelle Kunimoto | Email: mkuni@phas.ubc.ca 

Summary: There are multiple possible summer projects within exoplanet and/or Solar System science. Below are some examples, but these are not exhaustive. Some experience with Python is required for all projects. 
Project A: Transiting Exoplanet Photometric Follow-Up. Most exoplanets have been discovered using the "transit method", which involves looking for repeating dips in the observed brightness of a star due to a planet passing in front of the star and blocking a portion of the star's light. This project will involve observing exoplanet transits with the UBC Thunderbird South telescope for two primary purposes: (a) observing that the planet transits the star we expect, which is a crucial step towards planet confirmation, and (b) refreshing the planet's orbital ephemerides (period and transit times), which is crucial for planning time-sensitive follow-up observations such as atmospheric characterization with the James Webb Space Telescope. 
Project B: Multi-Survey Asteroid Light Curve Modelling. Wide-field surveys (e.g. the upcoming LSST, ZTF, WISE) are the largest sources of photometric data for asteroids. However, light curves from wide-field surveys are usually sparse in time and scarce in data volume per asteroid. Such light curves are often insufficient to infer even basic properties such as spin periods. This project aims to combine data from multiple wide-field surveys to build a large catalog of asteroid photometry – which could be leveraged to derive thousands of new asteroid rotation periods and possibly other more complex physical properties.

24. Summer USRA Project in Computational Materials Physics
Contact: Prof. Joerg Rottler | Email: jrottler@physics.ubc.ca

My group at QMI is looking for a summer USRA with interest in atomistic modeling and simulations of materials. Topics of interest might include block copolymer vitrimers, functionalized associative poiymers, and disordered multicomponent oxides. Good computational skills and an interest in condensed matter physics are required. 

25. AI-Driven Advancements in Nuclear Medicine: Optimizing Language Models for Clinical Reporting for PET scan
Contact: Arman Rahmim | Email: arman.rahmim@ubc.ca | Web: http://qurit.ca/

At the Quantitative Radiomolecular Imaging & Therapy (Qurit) Lab (Qurit.ca), our interdisciplinary team is dedicated to enhancing image analysis for Positron Emission Tomography (PET) scans with the ultimate goal of improving cancer diagnosis, staging, and therapy response assessment. We achieve this through close collaboration with nuclear medicine physicians, ensuring that our advancements are both clinically relevant and impactful.
Artificial Intelligence (AI) and large language models (LLMs), similar to ChatGPT, are rapidly transforming the field of radiology by excelling in tasks such as label extraction, summarization, and report generation from medical images. While LLMs have shown remarkable success across various domains, their optimization for nuclear medicine applications remains relatively unexplored. Preliminary efforts indicate that additional training on domain-specific texts, such as clinical reports in radiology, can significantly enhance their performance. However, adapting these models to the specialized vocabulary of nuclear medicine reports poses challenges in achieving accurate interpretation. Moreover, nuclear medicine physicians meticulously review prior reports to compose comprehensive evaluations, a process that advanced LLMs have the potential to streamline by summarizing existing data and generating concise clinical histories, thereby increasing both efficiency and accuracy.
Our long-term research plan at Qurit Lab focuses on evaluating and optimizing LLMs for nuclear medicine applications through several key initiatives. Firstly, we aim to assess the performance of language models in interpreting PET text reports for lymphoma cases, specifically targeting the generation of therapy assessments using the Deauville score. Secondly, we seek to fine-tune LLMs to produce accurate and personalized impressions for multi-institutional whole-body PET reports, ensuring consistency and reliability across different clinical settings. Lastly, we are developing models to generate comprehensive text reports based on PET scans, further automating and enhancing the reporting process.
The Student's Role:
We invite motivated co-op students to join our team and contribute to these cutting-edge research projects. As a co-op student at Qurit Lab, you will acquire proficiency in AI-based techniques and deep learning approaches through self-study and access to our extensive lab resources. You will engage directly with patient imaging data (PET/CT) and their corresponding reports, collaborating with our researchers to explore and refine language models tailored to the unique demands of nuclear medicine. Depending on your interests and expertise, you will participate in one or more of our key research initiatives, assisting in the fine-tuning of language models for interpreting imaging reports and generating treatment assessments using methods such as retrieval-augmented generation (RAG). Additionally, you will contribute to the generation of text reports based on PET scans, gaining hands-on experience in both AI and medical imaging.
The student's contributions will extend to various clusters within our lab, focusing on cancers such as lymphoma, cervical, prostate, and lung. You will be an active participant in our dynamic research environment, with opportunities to engage in AI competitions and contribute to conference and journal publications alongside our team members. Throughout the program, the co-op student will benefit from daily and weekly mentorship, immersive collaboration with clinical and technical experts, and a deep understanding of the latest developments in imaging and AI. Our lab fosters an environment that emphasizes effective communication and collaborative problem-solving, aligning with our commitment to mentorship driven by your eagerness to learn and excel.
Join us at Qurit Lab and embark on a transformative journey where your contributions will help shape the future of nuclear medicine imaging through innovative AI solutions. Apply now to become a part of our dynamic team and make a meaningful impact in the fields of cancer diagnosis and treatment. For more information about us, visit Qurit.ca.

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