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, including filament extrusion, compression molding, injection molding, and fused deposition modeling. This position requires the preparation of ISO/ASTM test specimens for mechanical (tensile and flexural
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Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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focus lies on a complementary approach of compression testing and high-pressure torsion deformation. The experiments are performed on hydrogen pre-charged, nanostructured metals and require analysis
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven
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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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Post-Doctoral Associate in the Center for Translational Medical Devices (CENTMED) - Dr. Panče Naumov
, compression molding, injection molding, and fused deposition modeling. This position requires the preparation of ISO/ASTM test specimens for mechanical (tensile and flexural) testing of polymers and composites
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of Swagelok installation, maintenance and reactor design principles. Experience in handling compressed or toxic gases. Skills 18. Demonstrable ability to plan and manage independent research.
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models for compressible hypersonic flows; implementing new models and numerical schemes into larger, existing hypersonic CFD codebases; performing verification & validation studies for the new models
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(Signal/channel generation, simulation environments, semantic compression, etc.), Semantic-aware Models and Explainable AI Proficiency in Python and machine learning frameworks such as PyTorch Hand-on