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Field
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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limitations or potential issues with datasets and data types that may impact performance from machine learning algorithms. Re-trains models as needed to address new challenges or novel goals. Aids investigators
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for facilitating effective communication with, and interaction between, the Hub’s various stakeholders, both internal and external. This will involve managing multiple communications channels and planning, creating
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in artificial intelligence (AI) for settings involving multiple interacting decision-makers---whether autonomous AI agents, humans, or a combination of both. Applications include mixed-autonomy
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stakeholders, both internal and external. This will involve managing multiple communications channels and planning, creating and distributing high quality content to promote the Hub’s activities and impact. This
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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responsibilities – position supports the Cancer Biology Program, with the expectation it will interface with multiple research teams with varied research interests, projects and timelines Qualifications Requirements
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. This includes: • Developing targeted campaigns that highlight faculty research, student success, and innovative programs—key metrics in ranking algorithms such as U.S. News & World Report, QS World University
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functional imaging to better understand disease pathophysiology, to discover new therapeutic targets, and to develop novel diagnostic algorithms that can improve patient care. Specific areas of research
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of developing algorithms that are both technically robust and clinically relevant, ensuring that these innovations can be integrated seamlessly into existing imaging systems and workflows. Collaborating with