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Date: Overview The hourly rate for this position is $22.39 per hour and is non-negotiable. Graduate Level 1 or above: Pursuing a Master's Degree or PhD in Computer Science, Electrical Engineering
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Sciences, Civil and Environmental Engineering, Physical Geography, and Biological Sciences or a related subject. • Interest in research in freshwater ecosystems, including machine-learning and
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to teach in at least one of the thematic areas listed above. Additional desired qualifications include a PhD degree, the ability to teach across multiple areas of the curriculum, strong engagement with
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engineered constructs. Learn more about the innovative work led by Dr. Chris Chen here: https://bdc.bu.edu/bdc-team/. What you’ll do: Independently conduct research on liver cell proliferation, expansion, and
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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PhD position in Human-Computer Interaction / Human-Centred Artificial Intelligence Help shape the future of work. This PhD project investigates how collaborative AI agents can support communication
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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Engineering » Electrical engineering Engineering » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Estonia Application Deadline 31 Jan 2026 - 23:59 (Europe/Tallinn) Type
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 15 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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-order modeling, or machine learning Experience collaborating in interdisciplinary research teams What you will do Develop hybrid quantum–classical methods to improve simulation and prediction