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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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are leaders in such disciplines as genome-editing, AI/machine learning, protein engineering, cryo-EM/ET, NMR, single-molecule experiments and more. You will also collaborate with the wider community at St. Jude
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above. Education in related fields such as data science, AI, computer science, machine learning, space engineering, Earth system science, climate, etc. would be an asset. Additional requirements In
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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area a wonderful place to live. Visit the Maine Office of Tourism to learn more about what the Bangor region has to offer. Qualifications: Required: PhD in Ecology, Geography, Data Science, or related
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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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University of Warsaw: Faculty of Mathematics, Informatics and Mechanics | Poland | about 2 months ago
comes with no teaching obligations BASIC RESPONSIBILITIES AND OBLIGATIONS Conducting research related to the scientific project titled “Calculus of variations in machine learning problems”, in particular
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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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-preserving and data-driven reduced order modeling scientific machine learning In addition to research, the postdoctoral researcher will engage in mentoring and outreach activities and will be expected to teach
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candidate with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental