*Updates for 2024 are in progress.

 

Supervisors

Andrea Kirkwood | Brad Easton | Dario Bonetta | Denina Simmons | Fedor Naumkin | Gregory Lewis | Jane Breen | Janice Strap | Jean-Paul Desaulniers | Joseph MacMillan | Kourosh Davoudi | Liliana Trevani | Mehran Ebrahimi | Olena Zenkina | Robert Bailey | Sean Bohun & Helene LeBlanc | Sean Forrester | Steven Livingstone | Theresa Stotesbury

 

Supervisor name: Andrea Kirkwood

Project title: Evaluating the effectiveness of aquatic vegetation removal methods in the Kawartha Lakes

Summary of research project: Excessive aquatic vegetation growth in the Kawartha Lakes is an ongoing problem that impacts the ecological and economic value of these waterbodies. Various techniques have been used over the years to control aquatic plant growth with mixed success. This Project is an exciting opportunity to compare conventional (mechanical harvester) and novel (bubbler, thruster) techniques for managing aquatic vegetation in the Kawartha Lakes, in partnership with Kawartha Conservation and Parks Canada. The goals of the study are to determine method effectiveness as well as their environmental impacts. This information will help to inform policies on aquatic vegetation management in the Kawartha Lakes.

Student responsibilities/tasks:

• The Student would work in a team environment, where each team member would be responsible for different research objectives.
• The Student assigned to this Project would conduct both field and lab work, where field observations will be collected at two lakes and plant and water samples would be processed back at the lab.
• The Student would record measurements and analyze the data to evaluate the study results.

Student qualifications required:

• The Student should be in their 3rd year of study in the Biological Science program at time of application.
• It is desirable that the Student is comfortable with the physical requirements of field sampling (carrying equipment, rainy weather, etc.) and are open to being trained to snorkel at lake sites to take underwater video/photos of plants.

Expected training/skills to be received by the Student:

• The Student will be trained in how to collect water and biological samples in the field. This involves learning how to use a multiparameter sonde, turbidimeter, discrete sampler, GoPro camera, transects, etc.
• The Student will learn how to process their water and biological samples back at the Ontario Tech lab. This will include chemical analyses for nutrients and chlorophyll, as well as some dissection microscopy to aid in identifying plants. The Student will also learn how to identify and distinguish different plant taxa.
• The Student will learn how to statistically analyze their data using a variety of computer software applications (Excel, SigmaPlot, R) as well as interpret their results.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Brad Easton

Project title: Advanced materials for electrochemical energy storage and conversion

Summary of research project: The development of conductive metal-oxide-based materials supports represent a unique platform for electrochemical energy conversion and storage applications. This Project will involve the synthesis and characterization of various nanostructured metal-oxide that are doped with different metals in order to modify their electronic properties and morphology. Detailed physical characterization will be performed to relate electrochemical performance with structure/composition.

Student responsibilities/tasks:

• The Student will work in collaboration with other team members on the synthesis and characterization of the materials. Materials characterization methods will include SEM, XPS, XRD, TGA, BET, and UV-Vis spectroscopy.
• In addition, the Student will be responsible for electrochemical testing and evaluation of the materials.

Student qualifications required:

• Successful completion of CHEM 3540U and CHEM 3040 is considered an asset.

Expected training/skills to be received by the Student:

• Nanomaterials synthesis
• Materials characterization
• Electrochemical measurements
• Analytical chemistry
• Surface chemistry

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Dario Bonetta

Project title: Phosphate transport in yeast.

Summary of research project: The proposed research will explore the interactions between proteins in phosphate homeostasis and signaling in yeast. The goal is to understand the interplay between how the phosphate status of the cell influences cell cycle events.

Student responsibilities/tasks:

• Student will work independently employing standard molecular and genetic techniques in yeast. Instruction will be provided.

Student qualifications required:

• Student must have a strong background in genetics and molecular biology.

Expected training/skills to be received by the Student:

• Competence in molecular biology techniques.
• Ability in designing and assessing experiments.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Denina Simmons

Project title: Measuring molecules in fish to understand the effects of forever chemicals on aquatic organisms.

Summary of research project: We will characterize groups of plasma proteins and metabolites that exhibit unique molecular expression patterns (MEPs) so that they can be specifically linked to a particular environmental adverse outcome pathway (AOP) and exposure to per- & polyfluoroalkyl substances (PFAS). These plasma MEPs could then be used as a diagnostic tool to identify exposure to PFAS. The objectives will (1) be to assist a graduate student when they sample epidermal mucus and blood plasma from fish in the environment and (2) to help prepare and analyze a sub-set of these field-collected samples for MEPs. This Project will complement an MSc project and will likely result in a peer-reviewed publication.

Student responsibilities/tasks:

• The Student will learn to collect blood and mucus samples from fish.
• The Student will assist with field sampling in streams and reservoirs.
• The Student will also work in the lab preparing samples for analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS).

Student qualifications required:

• Completion of Environment Biology, Ecology, or equivalent.
• GPA > 3.6
• Interest in freshwater biology and/or toxicology

Expected training/skills to be received by the Student:

• Collection of blood from fish
• Collection of epidermal mucous from fish
• Sample preparation for proteomics and metabolomics analyses
• Liquid chromatography tandem mass spectrometry

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Fedor Naumkin

Project title: Modelling molecular transformations in highly polar complexes

Summary of research project: New molecular systems and processes represent the essence of innovative chemistry research.
The Project's objectives include:

• Computational investigation of unique highly polar molecular systems in terms of stability, polarity, and other properties;
• Analysis of their isomerization and conformation-variation, evaluation of related energy barriers;
• Prediction of IR spectra to enable experimental detection of the systems and tracking of their structure evolution.

Such systems are relevant for a variety of applications employing light-matter interactions, molecular (self-)assembly, internal-electric-field mediated chemical reactions, molecular electronics and energy storage.

Student responsibilities/tasks:

• Explore and employ a computational chemistry software (under guidance of supervisor), prepare input files, run calculations on available high-performance computing facilities (accessed remotely via the Student's laptop).
• Analyze and visualize results by using a molecular-graphics software (to be learned as well), regularly discuss them with Supervisor.
• Do a literature search, prepare and deliver presentations at the Research Day, etc.

Student qualifications required:

• Preferred: completed CHEM 2010 with at least B-.
• Proficiency in main MS Office applications (Word, PowerPoint, Excel).
• Good calculus and geometry skills, good 3D imagination is a plus.
• Interest in computational research is a bonus.
• Familiarity with computational work in Linux environment is a super bonus.

Expected training/skills to be received by the Student:

• Hands-on experience in high-level molecular modelling using modern professional quantum-chemistry software at high-performance computing facilities.
• Development of practical skills in a prospective area of computational nanochemistry, adding a competitive edge for future work placement.
• Exercising the abilities to think independently, to directly check ideas via reliable calculations, to predict new species for guiding experiments.

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Gregory Lewis

Project title: Nonlinear Dynamics and the Atmosphere

Summary of research project: The Earth's atmosphere is a very complex nonlinear system that is influenced by many factors. However, the basic wind and temperature patterns, which are directly linked to changes in the climate, are primarily determined by the heating from the Sun and the rotation of the Earth. In this Project, mathematical models that highlight these primary factors are studied to learn more about how they induce transitions in the basic wind and temperature patterns. The models of interest are nonlinear differential equations, but are simple enough to allow for analysis using numerical approximation techniques.

Student responsibilities/tasks:

• In this Project, the Student will contribute to a research program that applies nonlinear dynamics techniques to simplified mathematical models of the atmosphere in order to study transitions in the basic temperature and wind patterns of the atmosphere. Specifically, the Student will work on their own project, which will be chosen to fit with the particular interests of the Student.

Student qualifications required:

• Must have completed at least two years of a mathematics or physics undergraduate degree or minor.

Expected training/skills to be received by the Student:

• Development of analytical and problem-solving skills. The Student will be required, with guidance, to formulate and solve research problems
• Development of communication skills. The Student will be required to communicate their findings with other members of the lab.
• Development of programming skills. The Project will involve programming.
• Knowledge building. The Student will acquire knowledge in mathematics and physics, relevant to the research problem

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Jane Breen

Project title: Graph centrality measures and dynamic processes in a network

Summary of research project: There are many real-world systems which can be represented by a network. By considering a network of individuals and their contact with one another, we can model the spread of disease in a community as a stochastic process on a graph. Similarly, one can model the spread of fake news in an online social network, or the movement of vehicles in an urban road network. The Google PageRank algorithm is based on a random walk on the web graph.

The research objective of the Student will be to produce a network model in their chosen domain of interest, and demonstrate how centrality measures may be leveraged to control/analyse the network and the phenomena it is used to model.

Student responsibilities/tasks:

• The Student will contribute to a research program that explores the applications of graph theory to a wide range of application domains. The specific area of application will be chosen by the Student based on their interests, background, and career aspirations.
• The Student will undertake some background reading on network science and graph theory, develop simulation models, and analyze and model real data using these techniques.

Student qualifications required:

• Minimum 3.0 GPA.
• Some programming experience is preferred, but not necessary.
• Discrete Math (MATH2080U/CSCI2110U) and some linear algebra preferred, but not necessary.

Expected training/skills to be received by the Student:

• Problem-solving skills and critical thinking
• Mathematical modelling
• Working with data to form and test conjectures
• Scientific writing skills, both formal (writing reports) and informal (writing blog posts, etc.)

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Janice Strap

Project title: Characterization of a regulatory protein involved in bacterial cellulose biosynthesis

Summary of research project: The Gram-negative bacterium, Komagataeibacter xylinus, synthesizes cellulose as an extracellular biopolymer important for host-microbe interactions. Despite decades of study, relatively little is known about the regulon that governs bacterial cellulose biosynthesis. This Project will investigate the role of a putative regulatory protein using molecular biology techniques and biochemical analyses.

Student responsibilities/tasks:

• Responsibilities include conducting experiments & documenting research activities in a laboratory notebook.
• Techniques that will be used in this Project include aseptic technique, bacterial culture, sterilization, sample preparation, mutagenesis, complementation, cloning, analytical biochemical assays, gel electrophoresis, polymerase chain reaction, DNA/RNA extraction.
• Students will be required to complete biosafety and WHMIS training.

Student qualifications required:

• Applicants are expected to have successfully completed BIOL 2060U and BIOL 3080U with a minimum grade of B+.

Expected training/skills to be received by the Student:

• Experimental planning and organization
• Documentation of research activities
• Data analysis and interpretation
• Standard laboratory practices, maintenance, and procedures

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Jean-Paul Desaulniers

Project title: Investigation of gene-silencing oligonucleotides

Summary of research project: Oligonucleotide-based drugs are revolutionizing modern medicine, and in the Desaulniers lab, we will be exploring the impact of chemical modifications on RNA structure and activity.  The objectives of the research will be to

1. synthesize new chemical modifications
2. evaluate their stability in cellular culture

A student in this role will be working closely with graduate students, and must have the flexibility and open-mind of exploring and conducting experiments in both organic chemistry and biology. For more information, please see our publications. 

Student responsibilities/tasks:

• Purifying organic compounds
• Conducting NMR experiments
• Growing cells
• Examine RNAs on cellular environments (stability, gene silencing, gene activation, etc.)

Student qualifications required:

• A student finishing third year in Biology or Chemistry is preferred. Overall grades of B+/A- average preferred. 

Expected training/skills to be received by the Student:

• Organic Chemistry
• NMR
• Cell culture
• Luciferase assays
• Time management

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Joseph MacMillan

Project title: Black Hole Growth in Dark Matter Halos

Summary of research project: Dark matter halos surrounding galaxies host supermassive black holes (BH). The growth of a seed BH affects the density at the centre of the halo; this has previously been studied under the assumption of adiabatic growth. This Project aims to expand the understanding of the role of BH growth by using N-body simulations to model the halo and BH together. The main objective will be to improve numerical resolution at the centre of the halo by using a new particle-mass scheme to better understand the role of the BH in those central regions.

Student responsibilities/tasks:

• Student responsibilities include adapting previous work in this field (e.g., updating numerical code to Python), researching and developing a new particle-mass scheme for N-body initial conditions, running and analysing simulations, and comparing results with previous work.

Student qualifications required:

• Completed PHY 2040U Mechanics II
• Astronomy background is preferred (e.g., taken PHY 3900U Astronomy II)
• Some coding experience preferred

Expected training/skills to be received by the Student:

• Programming and coding skills (Python, C, GitHub, Linux toolchains)
• Basic research skills (literature searches, reproduction of already-published results)
• Data analysis (large datasets, visualization, plotting)

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Kourosh Davoudi

Project title: Automatic Question Generation from Text

Summary of research project: The overall objective of the Project is to improve the technology for automatically generating questions and answers from text and demonstrating the system capabilities through a web interface. Extracting question/answer from text needs a significant amount of human effort. Over the past years, we have developed a few sentence-based neural question generation approaches. In this Project, we are going to 1) investigating paragraph-level methods. 2) developing an interface to visualize the outcomes of different steps and options. 3) providing mechanisms to capture the user feedback about the system-generated questions. 4) developing a web interface for the approach working at paragraph-level.

Student responsibilities/tasks:

• The backend techniques are built based on deep learning models and Semantic Role Labeling methods. Therefore, the Student needs to make themself familiar with these techniques and languages (e.g., PyTorch).
• The interface is supposed to extend and complete the prototype which has been already developed.
• The preferred language for developing the web interface is python, but using another language based on the preference could be an option.

Student qualifications required:

The Student should:

• Be in the 4^th year
• Have GPA >= 3.6
• Have competed Machine Learning (ML), and Data Mining courses
• Be familiar with Python
• Understand how to develop a web application
• Having some experience in PyTorch or TensorFlow is an asset

Expected training/skills to be received by the Student:

• The Student will understand the Natural Language Processing (NLP) pipeline and different tasks such as Part of Speech Tagging, Semantic Role Labeling, etc.
• The Student will have some hands-on experience on languages for developing deep Neural networks.
• The Student will learn how to demonstrate a research project through a web interface.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Liliana Trevani

Project title: Synthesis and characterization of nanomaterials

Summary of research project: The Project is expected to expand ongoing research work on the synthesis and characterization of nanomaterials for energy storage and conversion.  The main idea behind this initiative is to find materials that can be used as catalyst materials for the photo-electrochemical conversion of glycerol to chemicals, but other applications in the fields of sustainable energy and environmental remediation will also be considered.
As part of the Project, the Student will explore different synthetic approaches that are commonly used in our group for the optimization of the material’s composition, textural properties, and catalytic activity.

Student responsibilities/tasks:

• The Student will be responsible for preparing solutions, running experiments, preparing written reports, and presenting findings in group meetings.
• The Student will get training on several characterization techniques, from scanning electron microscopy, Raman and FTIR spectroscopy, thermogravimetric analysis, and nitrogen adsorption experiments to electrochemical methods. However, some of these experiments will be performed by a graduate student.

Student qualifications required:

• Any student who has completed the first year of the chemistry program with a minimum B+  grade can apply.
• The Student should enjoy working in the laboratory and pay attention to the assigned tasks, even when sometimes the experiments can be repetitive.

Expected training/skills to be received by the Student:

• The Student will take Health and Safety Training courses, and the Ontario Human Rights Code, the Accessibility for Ontarians with Disabilities Act (AODA) modules.
• Hands-on training in the use of a modern Raman spectrophotometer, and spectral analysis.
• The Student will get proficient in the use of standard laboratory equipment, and software.
• Synthesis of nanomaterials
• Characterization of nanomaterials
• Basic knowledge of applications of nanomaterials in the field of energy storage/conversion and the development of chemical sensors.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Mehran Ebrahimi

Project title: Machine Learning Techniques for Medical Image Fusion

Summary of research project: Several medical image processing techniques have been found to be useful for computer aided diagnosis (CAD). The goal of this Project is to extend and validate machine /deep learning algorithms aimed at multimodality image fusion. The research will be conducted at the Imaging Lab in the Faculty of Science, Ontario Tech.

Student responsibilities/tasks:

• The Student will be responsible for utilizing and extending our current image processing, machine learning, and data visualization tools and algorithms in either Matlab or Python.
• The Student will be engaged in literature review, mathematical modelling, programming, and validation of the results.
• In addition, the Student is expected to produce scientific reports of the results in form of a poster and/or a conference paper.

Student qualifications required:

• The Student is required to have a good understanding of calculus and linear algebra.
• In addition, programming skills in Python or Matlab is required.
• Experience working with imaging data, machine learning, and optimization is desirable but not required.
• Students in Computer Science, Mathematics, Physics, or a related field are encouraged to apply.

Expected training/skills to be received by the Student:

• Image Pre-processing
• Mathematical Modelling
• Numerical Simulations
• Data Analysis
• Document/Report/Manuscript preparation

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Olena Zenkina

Project title: Metal-Organic Functional materials

Summary of research project: EC materials are a class of ‘smart’ materials that reversibly change their optical properties under an applied voltage. They are used in smart windows/mirrors, battery charge sensors, and electro-optic modulators.  The Project will target preparation of novel efficient EC materials by integration of conductive metal oxide nanosurfaces with a monolayer of the metal complex resulting in durable materials with high coloration efficiency. It will involve organic synthesis of ligands, preparation and characterization of metal complexes, creation of the nanostructured supports and integration of all components into smart devices.

Student responsibilities/tasks:

• In addition to initial organic, organometallic and materials synthesis, the Student will explore chemical and electrochemical switching properties, stability, conductivity and colour efficiency of these novel materials.
• The ultimate goal will be to create functional materials with high coloration efficiency, colour homogeneity, high contrast ratios and controllable switching time.

Student qualifications required:

• Analytical chemistry, inorganic chemistry and organometallics, instrumental chemistry in asset.

Expected training/skills to be received by the Student:

• Inorganic and organic synthesis
• Methods for materials preparation and characterization
• Main strategies for studying and optimization of metal-ligand interactions on the surface support.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Robert Bailey

Project title: Using Drone Images to Quantify Aquatic Vegetation

Summary of research project: Aquatic vegetation can positively affect ecosystem health but negatively affect human use of freshwater ecosystems. We will test different means of managing aquatic vegetation using drone images to quantify the nature and amount of aquatic plant growth.

Student responsibilities/tasks:

• The Student will use a drone at several field locations to collect images of aquatic ecosystems.
• They will then use software to process and analyse the images and statistically compare aquatic vegetation among various management techniques.

Student qualifications required:

• The Student should have completed 3rd year in a BSc Biological Science program by Spring 2023 and be eligible and willing to do a 4th year thesis project on the research.

Expected training/skills to be received by the Student:

• Environmental science field research
• Drone flying licence and experience running drone missions
• Processing of drone images for analysis
• Download and processing of satellite images for analysis
• Analysis and interpretation of drone and satellite images

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Sean Bohun & Helene LeBlanc

Project title: You're Bugging Me!

Summary of research project: This Project will be concerned with the development and validation of mathematical models governing insect development and behaviour. Some possible examples include the growth of various of maggot species and the locomotion of adult flies. The work is with both a forensic scientist and an applied mathematician.

Student responsibilities/tasks:

• The Student will be tasked with reviewing the current literature, working to support the LeBlanc entomology lab, developing mathematical models, and validating them with either existing data or new data obtained in the lab and in the field.

Student qualifications required:

• At least a B average in their first two years of undergraduate studies.
• Completed at least one of STAT 2010U, STAT 2020U, STAT 2800U

Expected training/skills to be received by the Student:

• Learning to model biological systems from first principles
• Working within the confines of a forensics laboratory
• Demonstrate that they can effectively communicate professionally at the interface of forensics and mathematics

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Sean Forrester

Project title: Isolation of cys-loop receptor genes in Dirofilaria immitis

Summary of research project: A parasite important in Canada with the potential for higher prevalence due to climate change is the canine heartworm Dirofilaria immitis. Our laboratory conducts research on a large group of cys-loop receptors called ligand-gated chloride channels (LGCCs). However, despite a relatively large family of receptors, we know very little about how these channels contribute to the biology and parasitic lifestyle of D. immitis. This information is essential for determining whether these channels have potential as future nematocidal drug targets. This Project will investigate the biological role of the cys-loop LGCC family in D. immitis.

Student responsibilities/tasks:

• PCR
• Gel electrophoresis
• Plasmid gene cloning
• Bacterial transformation

Student qualifications required:

• BSc student in Biological Science.
• GPA or 3.7 or higher

Expected training/skills to be received by the Student:

• Student will learn basic molecular biology skills and proper techniques
• Student will learn how to troubleshoot experiments
• Student will gain a breath of knowledge related to molecular parasitology

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Steven Livingstone

Project title: Capturing expressive respiration

Summary of research project: Speech emotion recognition is a rapidly growing field in machine learning, leading to a new generation of human-computer interfaces. My lab is investigating a novel paradigm - Affective Breath Recognition (ABR) - the classification of emotion from audible respiration. In this Project, you will develop software required to capture respiratory patterns from participants. You will gain expertise in Python programming and cutting edge research packages, get hands-on experience with physiology recording hardware, and develop new methods of sending hardware-based triggers through software. Your work will be deployed in our lab’s new project on the capture and classification affective respiration.

Student responsibilities/tasks:

You will be expected to:

• Participate in weekly meetings with your supervisor
• Undertake independent learning of hardware and software packages
• Apply software testing procedures to ensure program correctness
• Make effective use of git for version control
• Present the outcomes of your URA to members of the Affective Data Science Lab (ADSL)

Student qualifications required:

• Completed 2nd year electives.
• Obtained a GPA of B+ or higher (>=77) for your 2nd year courses.

Expected training/skills to be received by the Student:

• Training in Python programming and cutting edge research packages
• Training in the use of physiology recording hardware and software
• Training in written and oral communication
• Training in the use of version control software

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR Award

 

Supervisor name: Theresa Stotesbury

Project title: Forensic bloodstain degradation in the environment

Summary of research project: Blood is a type of evidence encountered in crime scenes that can offer a variety of information important to criminal investigation. Understanding biomolecule degradation within a bloodstain is particularly important for building time since deposition models. Environmental considerations including temperature, humidity and light exposure all influence the rate of bloodstain degradation.

The URA Student will contribute to this research program in forensic chemistry by investigating how a range of environmental conditions influence bloodstain detection and/or degradation. 

Student responsibilities/tasks:

• This position is geared towards supporting research in forensic chemistry and materials science.
• The Student will work alongside graduate students and learn key skills in biological fluid preparation and characterization. (See training bullet points)

Student qualifications required:

• Seeking those with a background in forensic, analytical and organic chemistry.
• Knowledge of applied statistics is an asset.
• The Student should be task oriented, an independent and team player, have strong scientific literacy, creative, innovative and enthusiastic about science!

Expected training/skills to be received by the Student:

• Hypothesis development and testing using original experimental designs
• Safely working with biological materials for forensic simulations
• Operation of technical instrumentation including but not limited to: rotational rheometer, SEM, fluorimeter, optical profilometer, UV-Vis
• Data acquisition and interpretation
• Disseminating results in research meetings and writing reports

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR Award