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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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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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power of data science and algorithmic research with the fields of democratic theory, political science, and public policy. Ideally, the candidate has expertise and interest in innovative research using
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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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. The ultimate objective is to develop a next generation of AI approaches that are more sustainable and accessible. Relevant domains include mathematical and computational optimization, learning algorithms
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 24 hours ago
. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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/validate algorithms for medical images and perform data analysis using state-of-the-art software programming tools such as Python. They are also expected to write publications, liaise with collaborators