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                (qMRI) methods and applying these techniques to clinically relevant problems. Interested candidates are encouraged to apply and will join an active team focused on cutting-edge quantitative MRI method 
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                resonance imaging (qMRI) methods and applying these techniques to clinically relevant problems. Interested candidates are encouraged to apply and will join an active team focused on cutting-edge quantitative 
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                evaluation of alloys; familiarity with finite element methods. Skills and experience in programming, machine learning, or signal processing are all considered a plus. Outstanding UA benefits include health 
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                & Responsibilities Developing automated manufacturability analysis methods for additive and conventional manufacturing processes. Applying machine learning techniques to 3D engineering data (CAD models, meshes, voxels 
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                Responsibilities Research and scholarly activities: Conduct independent and collaborative research. Design experiments, develop models, and analyze results. Maintain accurate records of methods, data, and results 
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                of methods, data, and results. Present findings at internal group/project meetings. Publication and dissemination: Prepare high-quality manuscripts for major peer-reviewed journals. Contribute to conference 
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                -related folding is a strong asset, along with experience in fractured hydrocarbon reservoirs. Experience in other structural modeling techniques and software (numerical discrete element method 
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                experiments. Supervisory responsibilities and training for laboratory personnel in procedures and methods. Participate in the departmental intellectual community through attendance at journal clubs, seminars 
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                to proposal development and grant writing (including preliminary data, methods, budgets text); prepare progress reports, and coordination with internal/external collaborators; interface with sponsors where 
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                projects in AI-driven GNC for space robotics systems, leveraging both classical optimization techniques and modern machine learning methods. Lead and support research projects in AI-driven solutions for SDA