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Government of Canada | Government of Canada Ottawa and Gatineau offices, Ontario | Canada | 30 days ago
and proceedings, presentations at top conferences, and widely recognized contributions to software projects. • Designing, implementing and testing new algorithms or applications in one or more
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are filled. An earned doctorate is required by the start of the appointment, and a background check must be completed prior to beginning employment. Application materials should be submitted to http
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. Application materials should be submitted to https://www.mathjobs.org/ . The Georgia Tech official website for applications is https://hr.gatech.edu/careers . Some candidates who do not apply there at first
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the project’s deliverables. 2. To perform internationally competitive research in the analysis of transcriptomic and epigenetic data. 3. To provide analytical and statistical expertise, and algorithms for data
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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: January 19, 2026 (for full consideration) Apply online at AJO: https://academicjobsonline.org/ajo/jobs/31255 The Center for Data Science for Enterprise & Society at Cornell University seeks to recruit
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee Our department is looking for a Research
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algorithms will be used to assess how different neutrophil subpopulations directly and indirectly kill tumour cells, and how this behaviour is influenced by other cells in the tumor microenvironment. Analysing
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analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical
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reliable models and algorithms in these contexts (weakly supervised, semi- or unsupervised learning, domain generalization, active learning, federated learning, privacy preservation, noise and uncertainty