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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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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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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
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Nature Careers | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 26 days ago
learning, statistics, algorithm engineering, bioinformatics, or advanced data visualization. Evidence of effective participation and leadership roles in interdisciplinary research teams, teaching, and
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machine learning algorithms. It also serves as a foundation for more advanced ML courses. The students will learn about ML problems (supervised, unsupervised, and reinforcement learning), models (linear and