Summer 2020 Undergraduate Research Positions at Multimedia Laboratory in Computer Vision and Machine Learning Topics on Computational Pathology
The Multimedia Laboratory at the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto is seeking multiple Undergraduate Research Assistants in the area of Computer Vision and Machine Learning applied in Computational Pathology for the summer 2020 (May 1st – August 31st). The closing date for the applications is February 21st, 2020.
The Multimedia Lab (www.dsp.utoronto.ca) is an interdisciplinary research facility at the ECE department at UofT under the supervision of Professor Konstantinos N. Plataniotis. Successful candidates will work on an ongoing research project in Atlas of Digital Pathology (ADP) which is conducted jointly with Huron Digital Pathology Inc. and St. Michael’s Hospital. For more information please visit http://www.dsp.utoronto.ca/projects/ADP/. The outcomes of this project will be publications and release of the algorithms and codes.
As a Research Assistant, you will join a research team in Multimedia Lab for the execution of the research plans in Atlas project. We are particularly interested in the following topics:
• Explainable Architectural design of Convolution Neural Network (CNN) for ADP
• Domain adaption and transfer learning topics in computational pathology
• Disease categorization and classification of histopathological datasets
• User Interface(UI)-Cloud based designs for ADP data collection and compilation
The successful candidate will be preferably senior (third and fourth year) undergraduate student majoring in ECE, EngSci, or CS disciplines. However, exceptional candidates from second year undergrad will be also considered depending on the qualifications. All qualified candidates are encouraged to apply; however Canadians and permanent residents will be given priority.
The following lists the minimum criteria for qualification
• Related coursework in Machine Learning and Computer Vision
• Experience in Image data structures or algorithms gathered from: coursework projects, research, internships, or other practical experience inside or outside of school work
• Experience in Software Development and coding in programming language including but not limited to C++, Python (Pytorch/Keras/Tensorflow)
• Demonstrably good grades (at least 3.0, preferably 3.5+)
• Strong research motivation and willingness to learn on the job
• Excellent communication skills and willingness to work as a team
• Ability to speak and write English fluently and idiomatically
• Working hours are five days per week between 9:00AM to 6:00PM
The following also lists the preferred qualification criteria
• Returning to a degree program after completion of the summer research internship
• In-depth knowledge of Convolutional Neural Network (CNN) for image classification and weakly-supervised learning
• Existing understanding of medical histology and histopathology
Please note that the projects are highly demanding in terms of research effort and time dedication. The research assistants will be required to meet with their supervisor in a daily basis manner. The supervisor will be available to discuss challenges, provide guidance and assist with problem solving, and ensure the students are getting the appropriate support from the team and the project is on track.
Application Procedure
Interested candidates are required to prepare the following documents
a) Cover letter explaining your interest and why this position is a right fit to you
b) Resume
c) Soft copy of your (unofficial) transcript
Please submit them to Dr. Mahdi S. Hosseini by email mahdi.hosseini@mail.utoronto.ca. Applicants are highly encouraged to read the complete hiring post carefully prior to their contact and tailor their application documents according to the details of this hiring post.
Hiring interviews will be scheduled before the application deadline. The invited applicants for the interview will be asked to
- Prepare an essay report based on two scientific papers, which will be provided during the interview
- Send an example of coding in C++/Python
The successful candidates will be contacted for the next step application procedure. Please note that the positions will be filled as soon as suitable candidates are found.