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, Merced is looking for an ambitious Postdoctoral Scholar to carry out a project that leverages compressed sensing to accelerate proteomics research. The position is NSF-funded, and the scholar will work
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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, and lab inventories related to cellular and molecular biology techniques that will include common use items (e.g., compressed gas, dry ice and liquid nitrogen). Guide the work of others and/or provides
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device prototypes. Furthermore, the candidate should have experience in polymer processing techniques, including filament extrusion, compression molding, injection molding, and fused deposition modeling
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
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expectations. Preferred Qualifications Previous experience with turbulence over rough walls, porous media, or complex geometries, as evidenced by work history. Knowledge of compressible flow regimes, including
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of compressible flow regimes, including supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as
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setups, including: management of advanced laser systems, the design and construction of pulse compression systems, and building and operating optical characterization devices. Run existing simulation codes
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and training your own AI-based models for image segmentation or image compression, as demonstrated by Git repositories Experience in supervising students and young scientists Good knowledge of materials