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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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resources, funding, and mentorship Your Responsibilities: Lead the design, development, and optimization of scalable AI inference pipelines Implement and experiment with LLMs, GNNs, multi-modal AI, and vision
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develop and run the weather and climate model ICON. We are seeking a High Performance Computing (HPC) software engineer to further develop and optimize the ICON model (80-100%). Project background In order
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operations of the Office of the Vice President for Student Affairs. This role entails a mix of advanced administrative duties, project coordination, and key liaison activities, ensuring optimal office
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 7 hours ago
Long School of Medicine at UT Health San Antonio is accepting applications for our faculty position Disaster Medicine Fellowship. Optimal candidates will have completed an emergency medicine residency
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thesis, previous experience with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be
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with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be the workgroup of Prof. Dr
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, stochastic optimization, modern machine learning methods, scalable algorithms for advanced Machine Learning techniques and explainable AI.In teaching, the position will contribute, inter alia
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates
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experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in