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of acidic and aqueous media, impurity separation, and materials characterization to join a cutting-edge research team. The project focuses on developing sustainable and optimized processes
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work on plant genetics, growth strategies, and crop management with the aim of achieving optimal crop performance by integrating plant, environment, and management. The position offers close
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experience of mixed phase numerical or analytical flow modelling / solid mechanics / material characterization. Experience of analysing experimental data is highly desirable. You should have a record of
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
of microscopy, multiplexed immunofluorescence, spatial/protein imaging, or image-derived single-cell phenotypes. Machine learning, latent variable modeling, variational autoencoders, optimal transport, graph
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mass and extracted material and can thus provide engineers and decision makers with important information for safety and productivity optimization. Your mathematical, analytical and problem-solving
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, optimize, and test advanced materials that will accelerate the deployment of higher performance nuclear energy systems. As part of our research team, you will assess the viability of accelerated irradiation
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, anatomical, locomotor, and other behavioral data using appropriate computational and statistical methods. 5. Develops and optimizes experimental approaches to identify spared and reorganized supraspinal and
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scales from microchannels to full rack systems (5.) Develop physics and AI-based models to elucidate physics, perform optimization, and create surrogate models for system level simulators (6.) Participate
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actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and
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by ATi/Innovate UK and Rolls Royce and is fixed-term to October 2029. You will join a world‑leading programme advancing experimental and numerical methods for predicting the performance of 3D woven