Postdoctoral Fellowship in Computer Vision, Image Procession, and Deep Learning

Competition 880

This position offers a benefits package found at Postdoctoral Fellows Benefits.  

This full-time position has an initial appointment length of 1 year with the possibility of a 1-year extension and a compensation package of $60,000 annually which includes a stipend and research expenses.

Travel may be required.

Location - Work primarily takes place in person at North Campus, Edmonton. This position is not eligible for remote work. 

Working at the University of Alberta

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The University of Alberta is a community of knowledge seekers, change makers and world shapers who lead with purpose each and every day. We are home to more than 14,000 faculty and staff, over 40,000 students and 260,000 alumni worldwide.

Your work will have a meaningful influence on a fascinating cross-section of people — from our students and community members, to our renowned researchers and innovators, making discoveries and generating solutions that make the world healthier, safer, stronger and more just. Learn more.

About the Postdoctoral Fellowship

iClassifier in collaboration with the Optical Diagnostics Group (ODG) at the University of Alberta, and MITACS Canada is looking for a postdoctoral fellow to join our Research and Development team in the area of computer vision and image processing. The successful candidate is expected to start as soon as possible with a 1-year contract and will conduct industry-related research in smart agriculture product system design and development. The candidate should have experience with hands-on Python programming, deep-learning-based computer vision, classic image processing, image annotation, and data collection. 

Candidate Profile

The position requires a self-starting researcher with a proven record of accomplishments in the required fields. The candidate must demonstrate strong verbal and written communication skills. The candidate must be able to work and lead in both a team-oriented environment or as an individual. 

Duties

Work with other Computer Vision and Machine Learning engineers on high-impact projects and innovate new solutions to problems in the fields of Smart Agriculture

• Develop new data acquisition, data processing, and machine learning pipelines
• Research and development of computer vision and ML algorithms
• Design custom Neural Network-based and classical machine learning-based (KNN, SVM, DT, Random Forest) classification models
• Developing, maintaining, and testing features for new and existing applications
• Data collection and photography on the farm to acquire data for the project (should be comfortable with cows and livestock)
• Communicate effectively and professionally
• Writing progress reports and creating technical documentation and creating comprehensive product documentation
• After-hours work may be required

Minimum Qualifications

• The applicant should be within 4 years of their PhD date of graduation and must be legally entitled to work (or be eligible to apply for a permit) according to the relevant provincial legislation and regulations.
• PhD degree in Computer Science, Electrical & Computer Engineering, Machine Learning, data science or related disciplines
• 3+ years experience in applying computer vision and deep learning methods
• Strong coding and programming skills in Python plus maintaining high coding standards (Please share your GitHub/GitLab if available)
• Experienced with Machine Learning / Computer Vision libraries (OpenCV, NumPy, SciKit, SciPy)
• Extensive practical experience with modern deep learning frameworks (PyTorch or TensorFlow)
• Mastery of classical machine learning algorithms for classification, regression, and data preprocessing.
• Experience with classic image/video processing and computer vision
• Knowledge and experience with signal processing
• Experience in launching and running Python scripts on Linux and Cloud servers
• Ideally, you will have a basic understanding of Linux, Git, CUDA, and GPU
• A teamwork mindset is essential

Preferred Qualifications

• Prior experience in:
• working with 3D camera and 3D data analysis
• livestock assessment
• industrial working with machine learning, especially deep learning and neural networks
• gait analysis
• Familiarity with agile software development management
• Having related published papers
• Previous co-op or work experience in industry or livestock breeding farm
• Understanding and developing APIs in a microservice architecture (FastAPI, Docker, PyTest)

Application Instructions

To apply, the candidates must submit their application use this form. Link to the application form: https://docs.google.com/forms/d/e/1FAIpQLSdoauELVcsf1KFNZXj4yG965ZngJUT3G8ShyoMjPjwpFhmJjA/viewform

The attached file should be named: Application to PDF position - computer vision and the application package should contain a single PDF file with the file name in the format PDF_lastname_firstname.pdf containing the following:

1. A cover letter
2. A detailed academic CV including the names of a minimum of three references (including PhD supervisor)
3. Links of Github or Gitlab, LinkedIn, etc.
4. Any other supporting document related to the job

The review of applications will begin immediately, and applications will be accepted until the position has been filled.