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Field
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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networks. • Apply AI/ML and deep learning techniques for analyzing dense multimodal data in real time. • Integrate system-level solutions for interfacing with computers, smartphones, or AR/VR
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and management, machine and deep learning, as well as a solid understanding of wave phenomena and geophysical data analysis and imaging.
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record of delivering high-quality research and engaging external partners, you will bring curiosity, critical thinking and a deep interest in the relationship between storytelling, popular culture and
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, implementing, and optimising advanced AI algorithms, with deep proficiency in machine learning architectures, scalable model development, and high-performance code. The role holder will have the opportunity
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of Singapore (MAS) and NUS. SGFIN aspires to develop deep research capabilities in sustainable and green finance, provide thought leadership in the sustainability space, and shape sustainability outcomes across
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-organised Good leadership skills and a team player Able to work independently and collaborate in a highly diverse, multi-cultural and interdisciplinary team Adaptable and willing to enter into deep learning
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but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial and single-cell omics (transcriptomics
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
field A strong publication record in high-impact venues (NeurIPS, ICML, ICLR, AAAI, ACL, EMNLP, Nature/Science family, JAMA, Lancet Digital Health, or equivalent) Deep expertise in machine learning and/or
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CW and pulsed laser systems, spectrometers, high-resolution cameras, and delicate optical components are desirable Expertise in advanced data analysis techniques (Machine learning and Deep learning