Postdoctoral Fellowship in Computer Vision, Image

2 weeks ago

Edmonton, Canada University of Alberta Full time

**Department** Faculty of Engineering - Mechanical Engineering Dept

**Hours per week** **Posted date** May 2, 2024

**Closing date** May 31, 2024

**Position Type** Full Time - Trust Funded

**Description**:
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**
- The University of Alberta acknowledges that we are located on Treaty 6 territory, and respects the histories, languages and cultures of First Nations, Métis, Inuit and all First Peoples of Canada, whose presence continues to enrich our vibrant community._

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**

**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
- 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**
- PhD degree in Computer Science, Electrical & Computer Engineering, Machine Learning, data science or related disciplines
- 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**
- A cover letter
- A detailed academic CV including the names of a minimum of three references (including PhD supervisor)
- Links of Github or Gitlab, LinkedIn, etc.
- Any other supporting document related to the job

We thank all applicants for their interest; however, only those individuals selected for an interview will be contacted.

**Note**: This opportunity will be available until midnight May 31, 2024, Edmonton, Alberta local time.

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