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Field
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applications for a post-doctoral fellowship specializing in magnetic/electromagnetic separation in solid and liquid matrices. Applicants should have a thorough understanding of the principles of magnetic
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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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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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, 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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between objects. A common way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between
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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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through our online application portal before November 4th, 2025. Please do not submit compressed files. We will not consider applications sent via email or postal services. We will get in touch with you
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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
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Intelligence, Goal-oriented Semantic Communications, Internet of Things, Data Compression and analytics, and Tactile Internet. What we offer We offer a vibrant and inclusive research environment with a strong
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that reveal the biology behind challenging childhood diseases. Rare diseases affect 400 million people worldwide; most still lack answers. Autonomous AI can compress months of genomic and literature analysis