202 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" research jobs in Canada
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. Thrive in The Neuro’s open-science environment, fostering data sharing and interdisciplinary innovation. This position is covered by the AMURE Collective agreement. https://www.mcgill.ca/hr/files/hr
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Liquid Argon Calorimeter system. Use novel high-level synthesis approaches developed internally (based on functional programming abstractions), to optimize the implementation of machine learning models and
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: Experienced in applying machine learning and data science tools (TensorFlow, PyTorch, pandas, NumPy, Scikit‑learn) to analyze and model complex atmospheric and environmental datasets. Proficient in multi
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quickly and accurately. High degree of computer literacy including familiarity with Microsoft Word, Excel, Zoom, Teams. Ability to learn new software programs such as REDCAP. Organizational and
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style Attention to detail Clear oral and written communication skills Experience and Education BSc in a related field with relevant coursework 1-2 years additional experience Background in NLP, machine
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, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary
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-disciplinary areas of artificial intelligence machine learning big data and data analytics software and security mobility and autonomy The Presidential Postdoctoral Fellowship is proudly supported by generous
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biostatistics and epidemiology Expertise in quasi-experimental, econometric methods and other advanced methods (e.g., longitudinal data analysis, trial emulation, interrupted time series, machine learning
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networks, machine learning, Markov models and other computational approaches to biology are important. Familiar with analysis and data visualization. Enrolled in an undergraduate degree. Location
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posting details advertised on the UBC Career sites. At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning