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Field
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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processing, inverse problems and data science with emphasis on analysis, optimization, numerics and algorithmic solution Collaboration in interdisciplinary cooperation projects and third-party funded projects
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collaborator Dr. Cynthia Gerlein-Safdi (Civil and Environmental Engineering, Berkeley) and assistance from at least one PhD student. In person work is required, but a hybrid working arrangement may be considered
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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goals As a researcher in this project, you will work on mathematical models for describing the radio environment and to design algorithms for estimating, for example, the location and spectral
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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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%-100% effort. Qualifications All required qualifications must be documented on application materials. Required Qualifications PhD in Biomedical Eng., Computer Science/Eng., Electrical Eng., Math
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around 15 are PhD students. The work environment is open and welcoming, striving to provide each employee with the opportunity to develop personally and professionally. The field of solid mechanics relates