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Field
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related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core job duties include
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project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
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Institute for Research in Mathematical Sciences and the Principles of Intelligence (PrincInt: https://princint.ai/ ), housed within the Fields Institute's Centre for Mathematical AI. The fellowships support
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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) Mentor undergraduate and graduate students with their projects and teach how to use new instrumentation. 8) Contribute ideas for new research projects. 9) Stay informed of new literature related
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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About the Opportunity About the Opportunity: Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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is part of the ERC-funded project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD
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collaborators. The position is part of the ERC Starting Grant “Actively learning experimental designs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate
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on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software for maximum efficiency and usability