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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

FS project summaries

Supervisors

Christopher CollinsTheresa StotesburyJean-Paul DesaulniersFedor NaumkinJarek SzlichtaMehran Ebrahimi | Olena Zenkina | Sean ForresterJanice StrapBrad EastonGregory LewisAndrea KirkwoodJane BreenDario Bonetta 

 

Supervisor name: Christopher Collins
Project title: Designing New Selection Techniques for Digital Pens

Summary of research project: In this project, we will be investigating the use of digital pens for selecting objects in applications. Pen selection often uses a 'lasso' approach to select all the objects enclosed inside an area. This project will investigate new methods such as a 'crossing' approach to select objects the pen touches, a 'pressure' approach to select objects underneath other objects by pressing harder with the pen' and a 'selective' lasso approach, which selects only objects of the same type as the first one selected. This will allow efficient movement of objects in drawing and computer-aided design (CAD) applications, without requiring the user to switch between pen and other tools such as mouse/keyboard.

Student responsibilities/tasks:

  • The Student will be responsible for conducting a thorough literature review of existing pen-based selection methods.
  • The Student will create new web-based designs of pen-based selection mechanisms (pen hardware will be provided).
  • The Student will assist the supervisor in designing a remote-deployment (web-based) study to test the new methods with real participants, under REB approval.
  • The Student will attend weekly lab meetings.

Student qualifications required:

  • Completed at least second year computer science (third year preferred)
  • Web development skills - familiar with Javascript/HTML/CSS or confident to learn
  • Independent and excited to experiment with new ideas

Expected training/skills to be received by the Student:

  • Interaction design for pen+touch computing
  • Research methods in human-computer interaction
  • Reading and assessing research papers
  • Software development for interactive computing

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Theresa Stotesbury
Project title: Hydrogels for Forensic Tissue Simulants

Summary of research project: Hydrogel-based materials have demonstrated significant potential to be used as standardized tissue simulants. Their use is especially applicable for forensic research and training based on the relevant biochemical and mechanical properties. In this USRA project, the Student will expand upon our proof-of-concept research (https://doi.org/10.1016/j.forsciint.2021.111055) and further optimize our biomimetic materials to better simulate elastic tissue degradation in forensic scenarios. The Student will explore the role of crosslinkers and/or other additives on the rheological and optical properties of the soft-materials. This project will be co-supervised with Amanda Orr.

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 material preparation and characterization. (See training bullet points)

Student qualifications required:

  • Seeking those with a background in forensic, analytical and organic chemistry. Students without a relevant background in chemistry will not be considered.
  • Candidates should be task oriented, independent and team player, have strong scientific literacy, are creative, innovative and enthusiastic about science!

Expected training/skills to be received by the Student:

  • Operating technical equipment including, but not limited to: rotational rheometer, SEM, fluorimeter, optical profilometer, UV-Vis
  • Rheological, optical and spectroscopic assessment of dried and degraded materials
  • Conducting original experimental design, data acquisition and interpretation
  • Safe methods for solution preparation, materials creation, wet-bench chemistry
  • Disseminating results in research meetings

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Jean-Paul Desaulniers
Project title: Synthesis of Fluorinated Azobenzene Small Molecules

Summary of research project: The synthesis of a fluorinated azobenzene derivative is a switchable molecule that can isomerize between cis and trans in the presence of light. This molecule has utility when incorporated within biological molecules.  The objectives of the project for the summer student are to:

1. Synthesize the multi-step synthesis of the fluorinated azobenzene, using established protocols developed by our lab
2. Purify these compounds using chromatography or crystallization
3. Characterize the compounds using TLC and NMR

This project is best suited for a student with high interest in organic synthesis, preferably finishing third-year chemistry, and entering fourth year. 

Student responsibilities/tasks:

  • Perform organic reactions
  • Purify organic reactions
  • Characterize organic reactions
  • Write and organize in notebook
  • Be diligent, organized and motivated

Student qualifications required:

  • Ideally, completed CHEM 3120U.
  • GPA of B or higher.
  • Exceptional students finishing second year will be considered (A in CHEM 2120U).
  • Chemistry students will be given preference

Expected training/skills to be received by the Student:

  • Performing organic reactions
  • Characterizing organic reactions

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

  

Supervisor name: Fedor Naumkin
Project title: Modelling of Novel Supramolecular Species with Enhanced Stability, Polarity, and Optical Activity

Summary of research project: Design of new molecular compounds is the very essence of innovative chemistry research.
The project's objectives include:

  • Computational investigation of unique ion-pair enabled molecular systems in terms of stability, polarity, and other properties;
  • Analysis of their isomerisation and (noncovalent) 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 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 Science 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 superbonus

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.
  • Exercizing the abilities to think independently, to directly check ideas via reliable calculations, to predict new species for guiding experiments.

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Jarek Szlichta
Project title: Automatic Knobs Tuning via Deep Reinforcement Learning 

Summary of research project: Modern database systems such as IBM DB2 have dozens of ``knobs'' parameters (e.g., bufferpool, sortheap and parallelism degree) that heavily influence the performance. Since manual specification is cumbersome, we propose an automatic tuning system via deep reinforcement learning through actor-critic networks. We utilize transfer learning, as training machine learning models only on execution times of queries is prohibitively expensive for large workloads. Thus, we plan to train models first on the estimated costs of queries and then fine-tune it on execution times. We also translate high-dimensional query execution plans (QEPs) into a low-dimensional embedding vectors (QEP2Vec).

Student responsibilities/tasks:

  • Review of related work in automatic knobs tuning for database systems
  • Design large-scale machine learning driven approach to tuning
  • Implement the solution with the deep reinforcement learning model
  • Conduct comprehensive experimental evaluation over real-world datasets
  • Write a research paper to be submitted to one of the top-tier conferences in data science, such as VLDB, ACM SIGMOD, IEEE ICDE and EDBT.

Student qualifications required:

  • Complete two of the following courses before starting the project: Scientific Data Analysis (CSCI 2000U), Database Systems and Concepts (CSCI 3030U) and Big Data Analytics (CSCI 4030)
  • Have proven strong programming and algorithmic skills
  • The required GPA is >= B, however, the recommended one is >= A-

Expected training/skills to be received by the Student:

  • Learning how to comprehensively review the related work
  • Designing research framework to improve on the state-of-the art algorithms
  • Implementing deep reinforcement learning solutions
  • Quantifying experimentally benefits of the proposed framework on real-world data
  • Improving the communication and writing skills via weekly meetings/presentations and the conference paper submission

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Mehran Ebrahimi
Project title: Machine Learning Techniques for Medical Image Processing

Summary of research project: Several medical image processing techniques have been found to be useful for detection, diagnosis, and pre-surgical localization of tumours. The goal of this project is to extend and validate machine learning algorithms aimed at solving real-world inverse problems in the field of medical image processing. The research will be conducted at the Imaging Lab in the Faculty of Science, Ontario Tech.

Student responsibilities/tasks:

  • The potential candidate 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: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Olena Zenkina
Project title: Molecularly Defined 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 electrooptic modulators.  The project will target preparation of novel efficient molecularly defined electrochromic 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 times.

Student qualifications required:

  • Preferably 3rd or 4th year chemistry student.
  • Research experience will be an asset but not the main requirement

Expected training/skills to be received by the Student:

  • Synthesis and characterization of simple organic compounds
  • Synthesis and characterization of metal complexes
  • Preparation of molecularity defined materials
  • Full materials characterization of the materials
  • Manufacturing of the devices and performance testing

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Sean Forrester
Project title: Characterization of the Cys-Loop Receptor Family from Dirofilaria Immitis

Summary of research project: Dirofilaria immitis is a mosquito transmitted parasitic nematode that primarily infects dogs and is the causative agent of the debilitating disease called heartworm. For the past two decades the only preventative treatments for heartworm are drugs from the macrocyclic lactone family. However, there are now reports of resistance of this parasite to macrocyclic lactone drugs in certain regions. Therefore, there is a growing need for the development of new anthelmintics. The cys-loop family of receptors remains an attractive target for the development of future drugs. In this Project, the Student will be isolating and characterizing cys-loop receptor genes from D. immitis.

Student responsibilities/tasks:

  • Cloning of cys-loop receptor genes.
  • Expression in Xenopus oocytes for functional examination.

Student qualifications required:

  • Knowledge in molecular biology techniques.
  • Previous lab experience in a BSc program

Expected training/skills to be received by the Student:

  • Molecular biology techniques, bioinformatics.
  • 2-electode voltage clamp electrophysiology (if time permits).
  • RNA synthesis (if time permits).

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Janice Strap
Project title: Characterization of Cellulose-Related Regulatory Proteins

Summary of research project: Komagataeibacter species synthesize cellulose, an extracellular biopolymer important for host-microbe interactions. While the addition of exogenous phytohormones affects the physicochemical properties of cellulose, the contribution of host-derived signals to the regulation of cellulose biosynthesis is not yet known. This project will investigate the role of two-component regulatory systems in response to host-derived signals and the regulation of cellulose biosynthesis through extensive genetic, biochemical and proteomic analyses.

Student responsibilities/tasks:

  • Techniques include: bacterial culture, sterilization, sample preparation, mutant generation, complementation and characterization, organic extractions, sample clean- up, analytical biochemical assays, gel electrophoresis, TLC, column chromatography, PCR & qRT-PCR.
  • Students will be required to complete biosafety & WHMIS training.
  • A written summary of all research activities is expected at the end of the training term.

Student qualifications required:

  • Applicants are expected to have successfully completed BIOL 3032, BIOL 3080 with a minimum grade of B+.
  • Preference will be given to students who have also successfully completed BIOL 3010, CHEM 2030 and CHEM 3830.
  • Applicants should be familiar with basic laboratory skills in biological science & chemistry.

Expected training/skills to be received by the Student:

  • Learn experiment design, planning and execution.
  • Learn proper laboratory documentation.
  • Learn various data analysis techniques (wet lab and bioinformatics).
  • Learn various microbiological/biochemical laboratory techniques.
  • Gain experience with data interpretation and report writing.

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

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:

  • Chemistry majors.
  • 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

Available Award: Ontario Tech STAR Award or NSERC USRA

 

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 Research Project, the Student will contribute to a research program that applies nonlinear dynamics techniques to simplified mathematical models of the climate and atmosphere in order to study transitions in the basic temperature and wind patterns.
  • 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

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Andrea Kirkwood
Project title: Investigating Invasive Aquatic Macrophytes in the Kawartha Lakes

Summary of research project: Aquatic macrophytes (i.e., plants and macroalgae) are an important component of biological communities in lakes. However, macrophyte beds can also grow to nuisance levels in response to nutrient pollution. The Kawartha Lakes have endured excessive aquatic weed growth and the establishment of invasive species for many decades. In recent years, the non-native invasive macrophyte Nitellopsis obtusa (starry stonewort) has become a dominant member of the macrophyte community in the Kawartha Lakes. This project aims to improve our understanding of invasive macrophyte dynamics and interactions in the Kawartha Lakes in order to inform and improve management strategies.

Student responsibilities/tasks:

  • As part of a larger team of lake association partners, the Student will conduct field monitoring in select Kawartha Lakes, as well as collect aquatic macrophyte and water samples for processing in the Kirkwood Lab at Ontario Tech.
  • Having a personal water craft license is an asset, but not required.
  • The Student will be trained on all field and lab tasks, as well as data management and analysis.

Student qualifications required:

  • Due to the competitive nature of this award, students with a GPA of 3.0 or above and currently completing 3rd year in any Biological Science specialization are considered eligible to apply.
  • Students interested in turning this project into an honours thesis project are especially encouraged to apply.

Expected training/skills to be received by the Student:

  • Field data and biological sample collection
    • The Student will learn how to record field observations, operate multiparameter sondes, and how to collect water and biological samples
  • Lab processing and analysis
    • The Student would learn how to process lake water samples in the lab, including nutrients and water chemistry
  • Biological sample processing
    • In the lab, the Student would learn how to process and measure macrophyte biomass and possibly aquaculture
  • Data analysis and management
    • The Student would learn how to collect, curate, manage, and analyse field and lab data

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

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.

Strategies for controlling or monitoring spread in a network revolve around how 'central' a node is in the network, as well as the structure of the network (e.g. the number and density of connections), but methods for quantifying these ideas vary widely.

 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
  • 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

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Dario Bonetta
Project title:  Reverse Genetics Approach Toward Understanding Strigolactone Signalling in Moss

Summary of research project: How organisms respond to their external environment is central to their physiology and development. The moss, Physcomitrium patens, changes its growth in response to small molecules found in it external environment to optimize its growth characteristics. Although some of the molecular players in strigolactone responses are known, many other gene products have yet to be characterized. The project will involve creating mutations in genes identified using CRISPR-Cas so that the strigolactone related phenotypes can be assessed.

Student responsibilities/tasks:

  • The Student will be required to generate the appropriate gene constructs through molecular biology techniques.
  • Mutant generation will be achieved by transformation and assessment of the resulting transformants.

Student qualifications required:

  • The Student should have a strong foundation in genetics and molecular biology.

Expected training/skills to be received by the Student:

  • Recombinant DNA techniques.
  • Moss transformation.

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA