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Priorities: We seek applications across all AI domains, with emphasis on: Foundational AI : Machine Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers
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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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. Required Qualifications: An earned PhD in a life sciences related field, such as Molecular Biology, Microbiology, Genetics, etc. A minimum of five years of post-doctoral wet bench research experience
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senior lecturer qualified in the field of Optometry, who will contribute actively towards teaching and learning, research, and CPD development; in line with the vision, mission, and goals of the University
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well as an advanced diploma in Architecture. Responsibilities: The incumbent will be expected to be able to fulfil the responsibilities of an associate professor, which include the following: Facilitating learning
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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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, 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