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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | 43 minutes ago
range of imaging and video processing fields beyond medical imaging. The Research Associate will be at the forefront of developing algorithms that are both technically robust and clinically relevant
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algorithms for: Swine production: Early detection of health problems in pigs (respiratory diseases, abnormal behaviors) from video streams. Swine processing: Automated assessment of animal condition and
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of developing algorithms that are both technically robust and clinically relevant, ensuring that these innovations can be integrated seamlessly into existing imaging systems and workflows. Collaborating with
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applications across a wide range of imaging and video processing fields beyond medical imaging. The Research Associate will be at the forefront of developing algorithms that are both technically robust and
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of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records. Track
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learning algorithm for multi-omics integration 3) Maintenance of server / database (Linux environment) 4) Assisting other team members in data analytics 5) Presenting work in at least one conference in
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of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . HuMBL, a research lab within the SBME, specializes specifically in wearable sensor technologies and algorithm-driven health analytics to enhance
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, including algorithms, complexity, cryptography, and logic. The candidate's qualifications, experience and overall market demand will determine a candidate’s final salary offer. The salary for this position
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Sessional Instructional Assistant - MAT302H5F - Intro to Algebraic Cryptography (emergency posting)1
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 23 days agocryptography, from Euclid to Zero Knowledge Proofs. Topics include: block ciphers and the Advanced Encryption Standard (AES); algebraic and number-theoretic techniques and algorithms in cryptography, including
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred