Graduate student positions currently open for recruitment - Smith Engineering

Join over 125 faculty members and over 600 graduate students in Smith Engineering at Queen's University, Canada to solve the world's most pressing challenges. Once accepted, all full-time research graduate students at Smith Engineering are guaranteed funding for the default degree time (2 years for research Master's students (MASc) and 4 year for PhD students) as long as the student remains in good standing. For more information about Graduate Programs at Smith Engineering, please visit our Graduate Studies page. To apply for one of the positions below, contact the supervisor as indicated in each posting.

Note: this is not an exhaustive list, there are many more open positions. Contact faculty members directly to inquire about additional positions.

Critical Minerals

Supervisor(s): Dr. Fei Wang
Start date: May or September 2026.
Department: The Robert M. Buchan Department of Mining
Description: We are currently looking for highly motivated and independent doctoral students who enjoy working in a collaborative environment to join our group starting in May, September, or January. We welcome researchers with backgrounds in hydrometallurgy, minerals engineering, chemical engineering, environmental engineering and related fields for global electrification and clean energy transition. Current openings (with full scholarships) are listed below:

• Kinetics and Fundamental Study of Hydrometallurgical Extraction of Chalcopyrite and Pentlandite
• Research and Application of Selective Extraction of Low-Grade Sulfide Minerals
• Critical Mineral Recovery from Silicate Minerals and Laterite Nickel Ores Coupled with CO₂ Mineralization
• Recycling and Reuse of Lithium Batteries and Next-Generation Battery Precursor Production
• Sustainable Extraction and Production of Lithium from Spodumene

Please make sure you meet the minimum admission requirements

https://smithengineering.queensu.ca/mining/graduate/phd.html at Mining Engineering Department and https://www.queensu.ca/grad-postdoc/grad-studies/apply at Queen’s University.

Contact: fei.s.wang@queensu.ca
How to apply: Please contact Prof. Wang and include your CV, a brief statement (a short paragraph) of your interests related to our research, transcripts, English proficiency test results, and examples of your recent work. Availability changes frequently according to project needs and funding; however, we are always ready to meet the most outstanding candidates from all fields and areas of expertise!

AI and Machine Learning

Supervisor(s): Drs. Jason Olsthoorn and Leon Boegman
Start date: Fall 2026
Department: Department of Civil Engineering
Description: Accurate wave and ice modelling is essential for protecting ecosystems, ensuring regulatory compliance, and planning for climate change. By combining AI/ML with physics-based approaches, this research delivers faster, more reliable predictions that support sustainable freshwater management and informed decision-making.

Project Highlights:
• Build AI/ML models for ice cover
• Integrate with physics-based hydrodynamic models (MIKE3 FM, AEM3D)
• Simulate hydro-climatic scenarios under future climate projections

Required Qualifications:
• Background in Engineering, Applied Math, Physics, or related fields
• Proficiency in Python
• Experience with AI/machine learning
• Strong quantitative/numerical modelling skills

Desirable Qualifications:
• Experience with data visualization
• Interest in climate/freshwater environmental modelling
• Scientific communication skills
You will gain advanced expertise in AI/ML-based environmental modelling, publications, real-world impact via industry collaboration, and a diverse, inclusive research environment.
Contact: Jason.Olsthoorn@queensu.ca
How to apply: Email a CV with a statement of interest (Subject: AI/ML Ice Modelling). Application review will begin on Feb 27, 2026 and continue until the position is filled.

Supervisor(s): Dr. Zhixing Cao
Start date: Flexible start date
Department: Department of Chemical Engineering
Description: Cells, the fundamental units of life, operate through remarkably complex and stochastic biochemical networks. Understanding these processes is one of the great scientific challenges of our time. Our group is developing the AI-Aided Virtual Cell (AIVC): an affordable, interpretable, and biophysically grounded digital twin of living cells. This virtual cell will simulate molecular-level processes with unprecedented clarity, enabling us to explore how cells behave, adapt, and malfunction. With an accurate AIVC, we can transform digital insights into real biomedical impact – such as discovering new biomarkers to classify cancer types with precision, predicting cellular responses, and screening anti-aging or therapeutic compounds without expensive laboratory trials.
Depending on your background and interests, you may contribute to:
• Modeling stochastic biochemical reaction networks
• Designing interpretable machine-learning frameworks grounded in physical laws
• Using AI to accelerate biological discovery
• Analyzing single-cell data to connect digital predictions with real biological behavior
• Collaborating with clinicians to translate computational findings into medical insights
Motivated students with training in mathematics, physics, biology, computer science, data science, or clinical practice. Curiosity, creativity, and a passion for multidisciplinary research are highly valued.
If you are excited about building an AI system that can “think like a cell” and contribute to breakthroughs in biomedical science, we welcome you to join us.
Contact: z.cao@queensu.ca
How to apply: Interested candidates should submit the following documents in PDF format to z.cao@queensu.ca:
- Updated CV
- Cover letter highlighting research interests and relevant experience
- Academic transcripts from previous degrees

Supervisor(s): Il-Min Kim
Start date: As early as possible
Department: Department of Electrical and Computer Engineering
Description: I am recruiting multiple PhD students to join our highly productive AI research group, which recently published many papers in top AI conferences, including a NeurIPS 2025 Spotlight Paper. Our work focuses on Agentic AI, VLMs, LLMs, Integration of AI to physical systems (physical AI), and Safe AI. Requirements: Strong background in AI/ML and solid coding skills (e.g., Python, PyTorch/TensorFlow). Stipend: Very competitive. We foster a collaborative and inclusive environment and welcome applicants from equity-seeking groups. If you’re passionate about impactful AI research, I encourage you to apply.
Contact: ilmin.kim@queensu.ca
How to apply: Please email me your CV and supporting materials such as publications or transcripts.

Supervisor(s): Ali Etemad
Description: I’m looking for a passionate and motivated individual to join my research group at Queen’s University, Canada, for a PhD position. The position is hosted at the Human-Centered AI and Interactive Machines (Aim) lab (https://www.aiimlab.com). It is in the area of multimodal (time-series, language, etc.) foundation models.
The position offers:
- A fully funded PhD opportunity
- A collaborative and innovative research environment
- The chance to work on groundbreaking projects
- Access to state-of-the-art resources and personalized mentorship

Requirements:
- A master’s (or bachelor’s) degree in computer science/engineering, electrical engineering, mathematics, or a related field
- Previous research experience and publications in relevant areas
- Strong background in machine learning and deep learning
- Solid experience with programming languages such as Python, and ML frameworks (e.g., TensorFlow, PyTorch)
- Excellent problem-solving skills and a passion for research
- Ability to work independently and collaboratively in a multidisciplinary team
- Strong communication skills, both written and verbal

Contact: ali.etemad@queensu.ca
How to apply: please fill out this form: https://lnkd.in/gE6pGt3G

Biomedical Engineering

Supervisor(s): Yong Jun, Lai
Start date: Sept. 2026
Department: Mechanical Engineering
Description: We are currently seeking highly motivated Master’s and PhD students to join our team in developing next-generation microsensing technologies for rapid pathogen detection. Candidates with backgrounds in dynamics, MEMS, microfluidics, biomedical engineering, or related fields will be strongly valued. This is an exciting opportunity to contribute to impactful research at the intersection of advanced sensing, device fabrication, and infectious-disease diagnostics.
Contact: lai@queensu.ca

Supervisor(s): Carlos Escobedo , Peter Davies
Start date: September 2026 (or May 2026)
Department: Chemical Engineering; Biomedical and Molecular Sciences
Description: This is a Bruce-Mitchell Ph.D. position with special funding. The project aims to develop microphysiological models (organ-on-a-chip and microfluidics) to recapitulate key micro-environmental features found in the GI tract, to investigate the behaviour of bacteria and new strategies to tackle bacterial infection as alternatives to the use of antibiotics. The student will work in a multidisciplinary team, in collaboration with researchers from different departments at Queen's University, and from the Institute of Science Tokyo, Japan.
The ideal candidate will have experience in microfluidics and/or organ-on-a-chip technologies, as well as cell culture and cell handling, or demonstrate equivalent skills and transferable experience.
We welcome applications from all students and encourage those from equity-seeking groups—including Indigenous peoples, racialized communities, persons with disabilities, and LGBTQ2S+ individuals—to apply. We value diverse perspectives and are committed to fostering an inclusive and supportive environment.

Contact: ce32@queensu.ca
How to apply: If you are interested, please send your CV and transcripts to ce32@queensu.ca
Application deadline: 2/27/2026

Biomedical Mechatronics

Supervisor(s): Matthew Pan , Amy Wu
Start date: May 2026
Department: Electrical and Computer Engineering, Ingenuity Labs Research Institute
Description: We are recruiting a highly motivated PhD student to join the CINTHeA (Co-creating Intelligent Neuro-Technologies for Healthy Aging) initiative — a major multi-institutional research program spanning Queen’s University, York University, and Baycrest. The successful candidate will lead research and development on the CaRollator, an intelligent robotic rollator that provides physical assistance, gait stabilization, and continuous mobility monitoring for older adults.
The CaRollator is one of three flagship robotic platforms in CINTHeA (alongside the CareBot and CareChair) that will be deployed and evaluated with older adults through a rigorous co-creation process involving clinicians, caregivers, community partners, and end-users. Your work will directly contribute to improving mobility independence, reducing fall risk, and enabling early detection of mobility decline in real-world environments.
Project Highlights
- Develop and evaluate a physically assistive robot that integrates force sensing, gait stability modelling, and user-adaptive control strategies to support balance and endurance.
- Integrate advanced perception (RGB-D, pose estimation) and sensor fusion for real-time mobility assessment and fall-risk prediction.
- Implement autonomous and semi-autonomous behaviours, including safe navigation in complex indoor environments (retirement homes, LTC).
- Collaborate directly with Baycrest, Seasons Retirement Communities, and Oasis networks for iterative field trials.
- Work within an interdisciplinary team spanning robotics, biomechanics, neuroscience, clinical mobility assessment, and AI.
Key Responsibilities
- Design and prototype sensing and control modules for the robotic rollator.
- Develop gait- and stability-related algorithms using multimodal data (IMUs, force sensors, RGB-D, encoders).
- Implement user-adaptive assistance behaviours (brake assist, stability augmentation, intent modelling).
- Contribute to perception pipelines for long-term 3D body pose tracking in natural environments.
- Coordinate co-creation workshops and field evaluations with older adults and caregivers.
- Publish in top venues in robotics, HRI, rehab engineering, biomedical engineering, and AI.
Required Qualifications
- Bachelor’s or Master’s degree in Engineering, Computer Science, Robotics, Mechatronics, or related fields.
- Strong background in at least one of:
- robotics systems or mechatronic design
- machine design
- control systems
- machine learning / computer vision
- human–robot interaction
- biomedical or rehabilitation engineering
- Proficiency with Python and/or C++ and comfortable with embedded systems or hardware integration.
- Solid communication skills and willingness to collaborate closely with clinicians, older adults, and partner organizations.
- Curiosity, independence, resilience and professionalism.
We welcome applicants from equity-seeking groups.
Contact: matthew.pan@queensu.ca
How to apply: Please send the following to Dr. Matthew Pan:
- CV
- Brief statement of research interest
- Up to two relevant publications or project summaries
- Transcripts (official or unofficial)
Application deadline: 2/28/2026

Supervisor(s): Amy Wu , Shahirose Premji, Sandra Fucile, Matthew Robertson
Start date: January, May, or September 2026
Department: Mechanical and Materials Engineering (in collaboration with the School of Nursing and School of Rehabilitation Therapy)
Description: The overall objective is to design a breastpump for infant feeding assistance that maintains the mother-baby dyad. Tasks will scale depending on degree program and include:
- Co-develop a sensor and actuation system for infant supplementary feeding (ideally wearable)
- Attend co-creation group meetings and consult medical professionals to determine functional/engineering requirements
- Design and fabricate fluidic control, regulation, and sensing mechanisms, and combine into an integrated wearable system
- Technically analyze and assess the integrated systems
- Iterate and adapt designs/prototypes according to medical team experts and experimental results
Contact: amy.wu@queensu.ca
How to apply: Please apply according to the "Open Positions" tab at https://smithengineering.queensu.ca/directory/faculty/amy-wu.html
While we appreciate all applicants' interest, only those selected for an interview will be contacted. We welcome and encourage applications from all equity-deserving groups.

Supervisor(s): Amy Wu
Start date: January, May, or September 2026
Department: Mechanical and Materials Engineering
Description: The overall objective is to design a wearable measurement system that can detect fall risk and integrate the system into a trunk exoskeleton that can provide active correction or haptic cues for correction. Tasks will scale depending on the degree program
Design of a real-time measurement system for fall risk detection during walking across different terrain over long periods of time.
Tasks include:
- Development of a multi-sensor wearable measurement system that provides physiological information about the wearer’s gait and balance. The measurement system will be validated with in-lab motion capture systems to determine the accuracy and reliability of relevant measures.
- Multi-season outdoor data collection to measure real walking conditions with the measurement system over a long period of time.
- Development of a balance model that can be validated by the data, and leveraging the model to make a prediction of fall risk and corrective behaviors.
Design of a trunk exoskeleton that can provide both haptic and active feedback for fall prevention.
Tasks include:
- Incorporating appropriate haptic cues to indicate behavior corrections are needed.
- Designing a system that can move the trunk to physically correct behaviors that increase fall risk.
- Leverage the results from the real-time measurement system to design an appropriate controller and correction mechanism.
- Evaluate the efficacy of the two assistive modes (haptic vs active) with human studies.
- Validate the trunk exoskeleton with human studies.
Contact: amy.wu@queensu.ca
How to apply: Please apply according to the "Open Positions" tab at https://smithengineering.queensu.ca/directory/faculty/amy-wu.html
While we appreciate all applicants' interest, only those selected for an interview will be contacted. We welcome and encourage applications from all equity-deserving groups.

Supervisor(s): Amy Wu , Sachil Singh
Start date: January, May, or September 2026
Department: Mechanical and Materials Engineering
Description: This interdisciplinary project between Queen’s (engineering) and York (sociology) seeks to design health and well-being technologies that take into account disciplinary differences across the social sciences and engineering. The student will be primarily supervised by Dr. Wu at Queen’s but also be co-supervised by Dr. Singh and work in collaboration with his PhD student. Applicants should have a technical background in mechatronics or robotics and have a strong interest in interdisciplinary work to understand how technological design can affect society. The position is ideal for someone with an engineering background but is committed to understanding and mitigating biases in AI, robotics, and healthcare systems.
Tasks include:
- Research trips to York to work with co-supervisors and collaborators
- Contributing to empirical research that analyzes existing social robots, evaluates designer blind spots, and co-develops frameworks that centre lived experiences, ethical commitments, and real-world clinical needs.
- Receiving rigorous interdisciplinary preparation, including qualitative research methods, participatory design, critical data studies, ethical assessment of robotic systems, and knowledge-mobilization strategies.
- Co-authoring publications, presenting at national and international conferences, co-leading prototype development, and helping to design and host major research events.
Contact: amy.wu@queensu.ca
How to apply: Please apply according to the "Open Positions" tab at https://smithengineering.queensu.ca/directory/faculty/amy-wu.html
While we appreciate all applicants' interest, only those selected for an interview will be contacted. We welcome and encourage applications from all equity-deserving groups.

Electrochemistry, including Batteries and Carbon Conversion

Supervisor(s): Drs. Farzaneh Sadri and Cao Thang Dinh
Department: Mining Engineering and Chemical Engineering
Description: The transition toward electrification and renewable energy systems has led to a rapid increase in demand for critical metals used in battery technologies. Developing sustainable methods for recovering and recycling these materials is therefore essential for ensuring long-term resource security and reducing the environmental footprint of energy storage systems. This project focuses on sustainable battery recycling and metal extraction, integrating hydrometallurgical processes with electrochemical systems to develop advanced technologies for the recovery and purification of valuable battery materials. The research aims to contribute to the development of circular supply chains for critical metals and support the transition toward more sustainable energy technologies. Seeking an outstanding candidate currently based in Canada or the United States to apply jointly to the Queen’s Postdoctoral Researcher Competition (Application deadline May 1, 2026). If the application is successful, funding would be $70,000/year for 2 years.
The tasks of this postdoctoral position will include:
o Conduct research on hydrometallurgical and electrochemical approaches for sustainable battery recycling and metal extraction
o Investigate and develop innovative process routes for the recovery and purification of critical metals from battery materials
o Perform experimental studies, data analysis, and process evaluation related to sustainable metal extraction technologies
o Collaborate with research team members and contribute to mentoring graduate students and disseminating research results through publications and presentations

Requirements and Desirable Experience:
o Hold a PhD in electrochemistry, materials science, chemical engineering, hydrometallurgy, or a closely related field (completed before Sept. 2026)
o Research experience in electrochemical systems, hydrometallurgy, or metal extraction processes
o Strong experimental and analytical skills
o Experience in sustainable materials processing or battery recycling (desirable)
o Excellent written and verbal communication skills
o Ability to work independently and collaboratively in an interdisciplinary research environment
o Applicants must be external to Queen's University at the time of application

Contact: 15fs10@queensu.ca
How to apply: Interested candidates are invited to send their Curriculum Vitae (CV) and short statement of research interests to 15fs10@queensu.ca

Supervisor(s): Hoang Dang
Start date: January to April 2026
Department: Chemical Engineering
Description: We are seeking one curious, motivated, and collaborative PhD student to join our research program on next-generation rechargeable batteries. The Department of Chemical Engineering at Queen’s University offers a collaborative, multicultural, and inclusive environment, with access to state-of-the-art research facilities and a vibrant graduate community. The position is supported, providing a CA $35,000 per year for four years.
We are looking for candidates who demonstrate excellence, creativity, and commitment to high-impact research:
1. Education:
o Recent MASc/MSc in Chemical Engineering, Materials Engineering/Science, or a related field, ideally with a focus on energy storage materials.
o Strong academic record in electrochemistry, materials characterization, and/or nanomaterials.
2. Research Experience:
o Prior work in functional materials is preferred.
o Knowledge of Li-ion battery materials is advantageous.
o Publications in reputable journals are a strong asset.
3. Technical Skills:
o Familiarity with electrochemical and material characterization techniques (e.g., cyclic voltammetry, EIS, XPS, XRD, SEM).
o Hands-on experience with synthesis and fabrication of Li-ion electrodes or flow batteries is an asset.
4. Other Skills:
o Independent and self-driven work style, with creative problem-solving ability.
o Strong communication skills for both technical and general audiences.
We welcome applications from all qualified individuals and are committed to equity, diversity, and inclusion. We particularly encourage applications from women, visible minorities, Indigenous peoples, persons with disabilities, and LGBTQ2S+ individuals. Applicants requiring accommodation during the recruitment process are invited to contact hoang.dang@queensu.ca.
Contact: hoang.dang@queensu.ca
How to apply: Please include the CV with 2-3 reference contacts, transcripts

Department: Chemical Engineering
Supervisor(s): Dr. Rachel Baker
Description: The Baker Lab at Queen’s University is an interdisciplinary group dedicated to advancing sustainable chemical processes through innovative electrochemistry. Our team combines expertise in electrochemistry, organic synthesis, catalysis and chemical engineering to develop methods that reduce the carbon footprint of industrial processes. We are currently focused on electrochemical reactions to convert CO2 and biomass into valuable chemicals, offering a potential alternative to traditional, energy-intensive manufacturing processes. We are looking for a researcher to join our dynamic and collaborative team, where you will contribute to cutting-edge research while having fun and exploring exciting scientific challenges. In addition to hands-on lab work, you’ll have the opportunity to develop valuable skills outside the lab, including communication, teamwork, and leadership, which are essential for career growth. If you're passionate about sustainability and want to be part of a team that values creativity and collaboration, this is an amazing opportunity to make a real-world impact while growing professionally.
Contact: rachel.baker@queensu.ca
How to apply:Please send an email to Dr. Rachel Baker at the address provided with a cover letter, transcript and resume/CV in English.

Fluid Dynamics

Supervisor(s): John Kurelek
Department: Mechanical and Materials Engineering
Description: The Aerodynamics and Wind Energy Lab is looking for talented and highly motivated PhD students. Our group focuses on advancing wind energy and other renewable energy and fuel saving technologies through the study of aerodynamics. We specialize in experimental fluid mechanics, using a range of facilities and cutting-edge measurement techniques (PIV and PTV) to study the flow physics of individual components (wings, blades, and rotors), and fully integrated systems (aircraft, wind turbines, and wind farms).
We are pursuing two complementary research themes, and invite PhD applicants interested in the following projects:
1. Investigating airfoil boundary layer transition, separation and laminar separation bubble dynamics to enhance performance in low Reynolds number applications (small-scale wind turbines, low-speed aircraft)
2. Developing physics-informed flow control methods for separation control and stall mitigation on wind turbine blades.
Requirements:
- Completed (or close to completed) MASc or MEng in Mechanical Engineering (or related field).
- Experience in experimental fluid mechanics, demonstrated through past research, academic projects, work experience, etc.
- Proficiency in a high-level programming language for scientific computation, data analysis and visualization (MATLAB, Python, etc.)
All candidates are invited to apply. We particularly welcome applications from groups traditionally underrepresented in engineering, including women, Indigenous individuals, racialized individuals, individuals with disabilities, and of the 2SLGBTQ+ communities.

Contact: john.kurelek@queensu.ca
How to apply: Interested candidates should email Prof. Kurelek with [KURELEK APPLICANT] in the subject line and include: a 1-page cover letter highlighting research interests and relevant experience, a CV, and academic transcripts.

Supervisor(s): Mahmoud Alzoubi
Department: Mining Engineering or Mechanical Engineering
Project Description: Permafrost degradation poses a severe challenge for northern Canada. In the Northwest Territories, permafrost thawing leads to approximately $51 million in damages to public infrastructure each year, which accounts for 18.5% of the territory’s total infrastructure budget for 2020. This escalating threat jeopardizes the integrity of Arctic mining critical infrastructures such as pipelines, roads, runways, buildings, and hazardous-waste facilities.
This project proposes a renewable-energy-based artificial ground freezing (REB-AGF) system to counteract permafrost degradation. The novelty of the proposed system lies in a dual closed-loop thermosyphon design, en-hanced by phase change materials (PCMs) that store cold energy and enable continuous operation with zero external energy input. The research activities will be conducted with an integrated approach comprising design characterization, numerical simulation, and experimental examination. In general, the principle of using PCMs within a porous matrix is a challenging fundamental problem; it is intrinsically a nonlinear, multi-physics process. It involves transient, multi-phase heat and mass transfer and fluid mechanics within a porous periodic structure.
The successful candidate will work on developing and implementing numerical models to simulate the complex thermal and mechanical interactions occurring during the phase-change heat transfer in porous media. This novel framework aims to enhance our understanding of the temperature gradients, overall thermal conductivity, and the minimum thermal threshold needed to implement local thermal non-equilibrium hypothesis in a multi-component system of low and high thermal conductivity materials. This will ultimately leads to design and efficiency improvement in engineering projects.

Qualifications: Admissions to Queen’s University are competitive. To be a successful applicant, you must fulfill the essential criteria as outlined below:
– A Master’s degree (for the Ph.D. position) or a Bachelor’s degree (for the M.Sc. position) in Mining, Mechanical, or Chemical Engineering with an academic excellence.
– Strong theoretical background in the following areas: Heat transfer, Fluid mechanics, Numerical analysis, Computational Fluid Dynamics (CFD), Partial Differential Equations (PDEs), Optimization analysis.
– Demonstrable research experience in the form of research projects, intern-ships, conference presentations, journal publications, etc.
– Proficiency in at least one high-level programming language for scientific computation, data analysis, and data visualization, i.e., MATLAB, Python, or C++
– Excellent written communication and presentation skills
– Strong motivation to be involved in an industry-oriented project and willingness to learn new concepts/methods/computational tools
– Experience with Linux terminal and High-Performance Computing is con-sidered an asset
– Familiarity with commercial CFD software (Fluent/COMSOL) is a plus

Contact: mahmoud.alzoubi@queensu.ca

How to apply: Interested candidates should submit the following documents in PDF for-mat to Dr. Mahmoud Alzoubi at mahmoud.alzoubi@queensu.ca. Each document’s name should include the document type followed by the applicant’s name. For instance, the CV for an applicant named John Doe should be labeled as: CV JohnDoe; the email’s subject line should read: “Application for PhD (or MSc): John Doe.”
– Updated CV
– Statement of purpose (2 pages max ) detailing research interests and relevant experience.
– Academic transcripts from previous degrees.
– Contact information for at least two academic or professional references.
Only shortlisted candidates will be contacted for interviews.
Admission: The successful candidate is expected to formally apply to the MSc or PhD programs at the Departments of Mining or Mechanical Engineering, and fulfill the minimum admission requirements for MSc or PhD programs at Queen’s University.

High Performance Computing

Supervisor(s): Ian Karlin
Department: Electrical and Computer Engineering
Description: With the ending of Moore's law the number of processor types (GPU, CPU, TPU, Custom, etc.) available for data centre designs is increasing. How to design, program and use systems that take advantage of these options is becoming a complex challenge. The Beyond Moore's Lab has multiple positions at the Master's or PhD level investigating heterogenous system design and use. Areas of research include, modelling of system design, improved data collection and analysis from real systems, workload (AI and scientific) driven design, and API design for programming. Depending on the project work will include experimental systems, building of models, and/or data analysis. There will be opportunities on this project to collaborate with other professors at Queen's and with supercomputing centres. These positions are fully funded. All applicants are welcome to apply and underrepresented applicants including indigenous, black, individuals with disabilities, 2SLGBTQ+ and women, who have been traditionally underrepresented in Engineering are highly encouraged to apply.
Contact: Ian.Karlin@queensu.ca
How to apply: If interested send a CV and a paragraph stating your interest in the position and any experience you may have related to performance tuning of applications, knowledge of computer architecture, and design of experiments (scientific or computer science experience will be treated equally) to evaluate hypotheses to Dr. Karlin.

Supervisor(s): Ian Karlin
Department: Electrical and Computer Engineering
Description: With the focus on AI and large language models relative system capabilities are changing. Network latency is increasing, tensor compute is growing more rapidly than other GPU compute capabilities. The Beyond Moore's Lab has one position at the Master's or PhD level (PhD preferred) investigating the implications of these changes on other AI and scientific applications. Understanding what tradeoffs are being made in processor and network design and what would be possible if other decisions were made in how to allocate transistors on a chip. The position is fully funded. All applicants are welcome to apply and underrepresented applicants including indigenous, black, individuals with disabilities, 2SLGBTQ+ and women, who have been traditionally underrepresented in Engineering are highly encouraged to apply.
Contact: Ian.Karlin@queensu.ca
How to apply: If interested send a CV and a paragraph stating your interest in the position and any experience you have related to the research areas: modelling of system design, improved data collection and analysis from real systems, workload (AI and scientific) driven design, and API design for programming heterogenous systems to Dr. Karlin.

Supervisor(s): Ian Karlin
Department: Electrical and Computer Engineering
Description: Data centre power challenges are both straining electricity grids and limiting computational throughput. The Beyond Moore's Lab has two positions at the Master's or PhD level investigating power and energy efficiency on modern GPUs and other emerging architectures. Applicants will investigate how code optimization, hardware setting changes, and different architectures impact the energy efficiency and performance of systems in power limited environments at both the node and data centre level. Both AI and Scientific applications will be used in this research. If interested for PhD students there are opportunities to explore the societal impacts of data centre power use and its impact on society. These positions are fully funded. All applicants are welcome to apply and underrepresented applicants including indigenous, black, individuals with disabilities, 2SLGBTQ+ and women, who have been traditionally underrepresented in Engineering are highly encouraged to apply.
Contact: Ian.Karlin@queensu.ca
How to apply: If interested send a CV and a paragraph stating your interest in the position and any experience related to computer architecture, high performance computing systems, networking and application performance understanding to Dr. Karlin.

Human Factors

Supervisor(s): Mariam Guizani , Samuel Dahan
Start date: September 1, 2026
Department: ECE, Faculty of Law
Description: Organization Overview: The Conflict Analytics Lab (CAL) at Queen’s University is an academic research consortium at the intersection of law, computer science, and social science. Our current focus is OpenJustice.ai, an open platform for developing, testing, and deploying legal AI systems in collaboration with courts, law firms, and public-interest organizations. OpenJustice.ai provides a no-code interface that allows legal professionals and researchers to encode legal reasoning and integrate reliable data into AI systems. The goal is to advance trustworthy, transparent, and accessible legal technology build on high-quality data and expertise. Position Details: This fully funded PhD Position will be focused on the development of OpenJustice.ai, an initiative of the Conflict Analytics Lab at Queen’s University. The project currently collaborates with partners such as: National and International Full Service Law Firms; Judicial institutions; and Legal aid organizations (Pro Bono Ontario). Current applications include: Assisted dispute-resolution tools for employment and housing law; Court intake and evidence-assessment systems (e.g., deep-fake detection); and Legal document review and drafting. This PhD project focuses on the human and organizational aspects of building and sustaining open-source communities around OpenJustice. It explores how lawyers and legal organizations can contribute, share, and adapt custom AI models—built through OpenJustice’s no-code interface—to address specific legal tasks and practice areas. The research bridges software engineering, information systems, and socio-technical design to understand how to grow and sustain open, practitioner-driven ecosystems for legal AI. Requirements: Master’s degree in Software Engineering, Information Systems, Human–Computer Interaction, Business, Sociology, or a related discipline. Proven experience conducting qualitative (interviews, ethnography) and/or quantitative (survey, usage data) studies. Strong motivation for high-impact, independent research. Excellent communication and writing skills. Interest in open-source communities, digital collaboration, or socio-technical systems. Optional: Familiarity with Grounded Theory or interpretive qualitative methods. Experience in community-based or action research. Knowledge of open-source community research, software engineering, or information systems field studies. Key Responsibilities: Design and conduct interviews, surveys, field studies, and user studies with open-source contributors, legal professionals, and AI researchers. Analyze qualitative and quantitative data using rigorous methods (e.g., thematic analysis, grounded theory, statistical modeling). Collaborate with developers to co-design interventions and evaluate community engagement practices. Publish findings in top-tier venues (e.g., ICSE, CSCW, FSE, CHI). Benefits: A fully funded PhD position (typically 4–5 years). A collaborative, inclusive, and interdisciplinary environment within the Conflict Analytics Lab and Smith Engineering Opportunities to contribute to real-world open-source initiatives and publish at leading venues. Active engagement with a global research network on legal AI.
Contact: Mariam.guizani@queensu.ca
How to apply: Application Process: Please complete the Google Form and submit the following materials in a single PDF via the Google Form:

A 1–2 page motivation letter describing your research interests and fit with the project.

A CV including publications (if any).

Academic transcripts (Master’s and Bachelor’s).

Github Repository (if any)

Reference Letter (preferred) or contact details for two references.

Form: https://docs.google.com/forms/d/1vAKAjrE2gwN5orkasKRZ6cb8a3vDa9Uss-GL3bbunpI

The Conflicts Analytics Lab invites applications from all qualified individuals. Queen’s is strongly committed to employment equity, diversity, and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous people, women, persons with disabilities, and 2SLGBTQ+ persons.

All qualified candidates are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents of Canada will be given priority.

Join us in shaping the future of legal AI research with the Conflict Analytics Lab!
Contact: For questions or to discuss your application, please reach out to: Dr. Mariam Guizani (mariam.guizani@queensu.ca) or David Liang (david.liang@queensu.ca).

Polymers

Supervisor(s): Robin Hutchinson
Start date: September 2026
Department: Chemical Engineering
Description: Project 1: Manipulation of Polymer Microstructure through Controlled Branching.
Acrylic resins manufacturers continue to seek improved process efficiencies by reducing solvent contents and usage of both material and energy. My group has demonstrated the ability to make higher-value acrylate block copolymers using a sequential feeding strategy in the same semi-batch reactor infrastructure employed to produce random copolymers. The new project will add low levels of crosslinking agent to the system, to expand the range of architectures that can be synthesized, and to reduce solvent content from its current 35 wt% level, as branched polymers have significantly reduced viscosities compared to their linear counterparts.
Project 2: Incorporation of Biosourced Monomers to Acrylic Resins
As polymeric coatings are used to extend material lifetime, biodegradability is not desired. However, the overall sustainability of these polymers can be increased by substituting non-renewable petroleum-based feedstocks with bioderived monomers. We have shown that the commercially-available bio-sourced dibutyl itaconate (DBI) can be effectively incorporated into acrylic resins at levels up to 50 wt% with butyl acrylate (BA) as comonomer while maintaining competitive overall polymerization rates. The new project will aim to further increase the sustainable content of acrylic resins by exploring the copolymerization of functional itaconate monomers with new acrylate monomers synthesized using alcohols from renewable feedstocks.

Contact: robin.hutchinson@queensu.ca

Power electronics

Supervisor(s): Yan-Fei Liu
Department: Electrical and Computer Engineering
Description: Our research group is seeking highly motivated graduate students to join cutting-edge projects in Electric Vehicle (EV) power systems and data center power systems. The research focuses on advanced power converter technologies, including high-efficiency and high-density solutions.
Candidates with knowledge or experience in one or more of the following areas are encouraged to apply:
• Power converters (topologies, control, and design)
• PWM and resonant converter techniques
• MCU-based systems and digital control implementation

This is an exciting opportunity to contribute to impactful, real-world applications in power electronics.
Contact: yanfei.liu@queensu.ca
How to apply:Please send your information to Dr. Yan-Fei Liu at the email address above

Robotics

Supervisor(s): Matthew Pan
Start date: May 2026
Department: Electrical and Computer Engineering, Ingenuity Labs
Description: The Machine Intelligence and Human–Robot Interaction Laboratory (MItHRIL) invites applications for a fully funded PhD position in Human–Robot Interaction, with a research focus on expressive robotic characters, artistic interaction, and performance-driven robot behaviour. The position is supported by the Connected Minds (https://www.yorku.ca/research/connected-minds/) initiative through the Creative Collectivities project, an interdisciplinary collaboration among researchers at Queen’s and York Universities and community-based artists. This project integrates robotics, neuroscience, and live performance to investigate expressive movement, shared agency, and technology-mediated interaction.
The successful candidate will contribute to the design, implementation, and evaluation of expressive behaviours for humanoid and manipulator robots, particularly in settings involving artistic collaboration, performative character interaction, and emotionally legible movement. The PhD researcher will be based at the Ingenuity Labs Research Institute (https://ingenuitylabs.queensu.ca), an interdisciplinary environment at Queen’s University dedicated to advancing AI, robotics, and human–machine interaction to enhance human capability, safety, and quality of life.
We welcome applicants from engineering, computer science, robotics, HRI, or related fields with interests in expressive or socially interactive robot behaviour. Preferred skills or experience include:
- Robotics (control, motion generation, or tele-operation)
- Human–robot interaction or social robotics
- Machine learning for motion or behaviour modelling
- Real-time systems (Python, C++, ROS/ROS2)
- Experience or interest in movement, performance, or embodied interaction
Required Qualifications
- Bachelor’s or Master’s degree in Engineering, Computer Science, Robotics, Mechatronics, or a related discipline.
We strongly encourage applications from members of equity-seeking groups. Curiosity, independence, professionalism, and a capacity to work across disciplines are essential. Competitive candidates will show strong interest in how humans perceive and interpret robotic movement and how robots can support meaningful artistic or narrative expression.
Contact: matthew.pan@queensu.ca
How to apply: Please send the following to Dr. Matthew Pan:
- CV
- Brief statement of research interest
- Up to two relevant publications or project summaries
- Transcripts (official or unofficial)
Application deadline: 2/28/2026

Supervisor(s): Jonathan Gammell
Description: I am looking for passionate and motivated individuals to do their M.A.Sc. or Ph.D. in autonomous and/or mobile robotics in the Estimation, Search, and Planning (ESP) research group. All interested applicants are encouraged to apply, including women and other members of groups that are underrepresented in robotics.
Contact: gammell@queensu.ca

How to apply: Please read and follow the instructions on the ESP website: https://robotic-esp.com/join/

Smart Mining

Supervisor(s): Asli Sari , Qian Zhang
Start date: January or May 2026
Department: Mining
Description: Intelligent Mining Systems (https://lnkd.in/e8H_y8wQ) and GreeMVC (https://lnkd.in/e8-s5rtN) labs at Queen's University are seeking graduate students to join us in January or May 2026 for an industry collaboration project on improving haul truck dispatch. This is an interdisciplinary project in which the researchers will work on improving the existing system and increasing its robustness. Our groups' previous work on the subject includes these publications: https://lnkd.in/ekXWDxeT and https://lnkd.in/ehxkntWT
Requirements:
- Analytical, problem-solving mindset
- Bachelor's, Master's or PhD degrees in mining, mineral processing, software, computer, environmental engineering or related fields, obtained by the start date
- Excellent programming skills in Python
- Ability to work independently and contribute effectively to a collaborative research team
- High motivation and a strong interest in applying machine learning techniques to real-world mining challenges
- Strong written and oral communication skills

Assets:
- Having work experience in an internship/co-op position in mining operations
- Experience with machine learning frameworks (Tensorflow or Pytorch, Scikit-learn)
- Solid foundation in reinforcement learning

Contact: y.sari@queensu.ca
How to apply: This is a funded position. If you are passionate about programming, machine learning, interested in solving real-world mining problems that will help the environment and would like to join our group, please send an e-mail with your resume and a cover letter to y.sari@queensu.ca and qian.zhang@queensu.ca. While we appreciate all applicants’ interest, only those selected for an interview will be contacted. We welcome and encourage applicants from equity-seeking groups.

Software Engineering

Supervisor(s): Ying Zou
Department: Electrical and Computer Engineering
Description: We are looking for motivated PhD students who are interested in applying artificial intelligence and Large Language Models into the software development process and help improve developers productivity. Financial support is provided to the candidates. We welcome applicants from equity-seeking groups.
Contact: ying.zou@queensu.ca
How to apply:send CV and transcripts

Supervisor(s): Mariam Guizani , Samuel Dahan
Start date: September 1, 2026
Department: ECE, Faculty of Law
Description: Organization Overview: The Conflict Analytics Lab (CAL) at Queen’s University is an academic research consortium at the intersection of law, computer science, and social science. Our current focus is OpenJustice.ai, an open platform for developing, testing, and deploying legal AI systems in collaboration with courts, law firms, and public-interest organizations. OpenJustice.ai provides a no-code interface that allows legal professionals and researchers to encode legal reasoning and integrate reliable data into AI systems. The goal is to advance trustworthy, transparent, and accessible legal technology build on high-quality data and expertise. Position Details: This fully funded PhD Position will be focused on the development of OpenJustice.ai, an initiative of the Conflict Analytics Lab at Queen’s University. The project currently collaborates with partners such as: National and International Full Service Law Firms; Judicial institutions; and Legal aid organizations (Pro Bono Ontario). Current applications include: Assisted dispute-resolution tools for employment and housing law; Court intake and evidence-assessment systems (e.g., deep-fake detection); and Legal document review and drafting. This PhD project focuses on the human and organizational aspects of building and sustaining open-source communities around OpenJustice. It explores how lawyers and legal organizations can contribute, share, and adapt custom AI models—built through OpenJustice’s no-code interface—to address specific legal tasks and practice areas. The research bridges software engineering, information systems, and socio-technical design to understand how to grow and sustain open, practitioner-driven ecosystems for legal AI. Requirements: Master’s degree in Software Engineering, Information Systems, Human–Computer Interaction, Business, Sociology, or a related discipline. Proven experience conducting qualitative (interviews, ethnography) and/or quantitative (survey, usage data) studies. Strong motivation for high-impact, independent research. Excellent communication and writing skills. Interest in open-source communities, digital collaboration, or socio-technical systems. Optional: Familiarity with Grounded Theory or interpretive qualitative methods. Experience in community-based or action research. Knowledge of open-source community research, software engineering, or information systems field studies. Key Responsibilities: Design and conduct interviews, surveys, field studies, and user studies with open-source contributors, legal professionals, and AI researchers. Analyze qualitative and quantitative data using rigorous methods (e.g., thematic analysis, grounded theory, statistical modeling). Collaborate with developers to co-design interventions and evaluate community engagement practices. Publish findings in top-tier venues (e.g., ICSE, CSCW, FSE, CHI). Benefits: A fully funded PhD position (typically 4–5 years). A collaborative, inclusive, and interdisciplinary environment within the Conflict Analytics Lab and Smith Engineering Opportunities to contribute to real-world open-source initiatives and publish at leading venues. Active engagement with a global research network on legal AI.
Contact: Mariam.guizani@queensu.ca
How to apply: Application Process: Please complete the Google Form and submit the following materials in a single PDF via the Google Form: A 1–2 page motivation letter describing your research interests and fit with the project. A CV including publications

Water and Pipeline Infrastructure

Supervisor(s): Dr. Geoff Eichhorn
Start date: May/September 2026
Department: Civil Engineering
Description: From the moment we wake up, Canadians subconsciously rely on buried pipeline infrastructure, to deliver clean drinking water for their morning coffee, remove waste through sanitary sewer systems, and provide energy to control room temperature. However, the public is largely unaware of their existence until something goes wrong. The long-term goal of this research program is to develop engineering solutions and highly trained personnel to protect Canada’s water, sewer, and energy pipeline networks against rupture from climate-driven permanent ground deformation.
Graduate projects (both MSc and PHd) include topics such as:
1) measure the soil-structure interaction of buried pipes in sloping ground composed of clay soil, for legacy infrastructure as well as new pipe construction.
2) assess the impact of ground movement caused by expansive soil (clay rich) for buried pipes, and how these conditions are influenced by climate-driven wetting/drying cycles.
3) evaluate the impact of freeze/thaw cycles due to climate change on the soil-structure interaction for buried linear infrastructure. These short-term objectives form the starting point for establishing best practices for buried pipe construction protection against climate change.

Contact: geoff.eichhorn@queensu.ca
How to apply: Please include an up to date CV including any work experience.
Note: Please include the reference number in your email subject line ‘CS-2026-87501’, with no quotations.