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Field
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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their practical deployment. The Project: This PhD will develop the science and engineering required to overcome these bottlenecks, with the following objectives: • Uncover the mechanisms driving enhanced hydrogen
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University of Southern California (USC) | Los Angeles, California | United States | about 1 month ago
inflammation. The ideal candidate is a passionate and driven scientist who thrives in a collaborative, fast-paced academic environment. A strong research background, outstanding writing skills, and the ability
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quantitative research expertise with deep trading intuition to build and refine data-driven, fully automated trading strategies. You’ll actively monitor real-time strategy performance and use market behavior and
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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renewable energy, AI-driven engineering, and industrial research. Cranfield’s expertise in wind energy systems, predictive maintenance, and AI applications provides an ideal environment for cutting-edge
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, and state-of-the-art infrastructure. Our model empowers visionary leaders to accelerate drug development and harness AI-driven innovation to address unmet medical needs. Benefits of Working with Great
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular