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Field
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever-changing and fast-paced sector. The position is funded by CAR, a
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technology and develop human resources. The AI Computing Team explores the design and realization method of advanced machine learning systems by working across multiple layers, including circuits, devices
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Engineering, Aerospace Engineering, or a related field. Degree must be conferred upon hire. Preferred Qualifications Applied expertise in optimal control, heuristic optimization, graph search algorithms, and
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algorithms, and machine learning to solve complex aerospace engineering challenges. Developed and implemented AI-driven solutions for autonomous lunar and asteroid landings, as well as cislunar operations
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, Prof Anton van den Hengel and his research team to publish research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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large quantities of data to gain a greater understanding of our systems and develop data analytics and artificial intelligence algorithms. You will be actively engaged in the research and development
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Description The Quantum Information team at UMass Amherst is involved with modeling and optimization of quantum hardware, as well as development of new modeling methods and algorithms, in collaboration with
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| Mechanical and Aerospace Engineering Perform basic research in computational fluid dynamics, including problem setup, simulation and advanced post-processing for multiple projects. Emphasis to be placed