22 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" uni jobs at Nature Careers in South Africa
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science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more
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Thrusts instead of Schools and Departments, it is geared to promoting interdisciplinary learning in a restless search for innovative solutions to humanity’s major challenges. HKUST(GZ) boasts cutting-edge
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, networks and communication systems, theory of computation, computing paradigms, AI and machine learning, numerical computing, and applied computing. In particular, beyond surveying individual fields and
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: https://www.apctp.org . JOB DESCRIPTION & ELIGIBILITY The Asia Pacific Center for Theoretical Physics (APCTP) invites applications for the Young Scientist Training (YST) Fellowship. This position is
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. The position is open till a successful candidate is selected. Submitted materials will not be returned. Background information regarding this position and the NCGWR can be found at the website: http
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Chair of the Scientific and Technical Advisory Panel (STAP) to the Global Environment Facility (GEF)
, strategies, programs, and projects. STAP (https://www.stapgef.org) is hosted by UNEP’s Office of Science and comprises a Chair and six Panel Members, each aligned with a GEF focal areas: biodiversity, climate
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The Institute of Biomedical Sciences at Academia Sinica, Taiwan (https://www.ibms.sinica.edu.tw/ ), a leading biomedical research institute in Asia, invites applications for tenure-track positions
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, including approaches that produce “black box” data that might only be actionable in conjunction with AI and machine learning methods. Experimental technologies could cover (but are not limited to) single-cell
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Learning, AI-driven Scientific Discovery & Lab Automation, ML-driven molecular simulations, and beyond. We will support our Starting Principal Investigators with access to appropriate compute infrastructure
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models (e.g., deep learning, reinforcement learning, probabilistic graphical models) for applications in genomic prediction, GWAS, GS, gene-editing target discovery, and multi-trait selection. Conduct