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, embracing failure as a learning opportunity, and continuously enhancing our knowledge and methods to tackle local, national, and global challenges. The postdoctoral associate will work directly with both
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there are also opportunities within facility operations, project management, and other mission support functions. To learn more about ongoing projects, you may visit the NETL website and browse news, core
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(e.g. Python, Julia), You have an interest in, or experience with, machine learning approaches for scientific data analysis. You have a strong interest in interdisciplinary research and enjoy
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 22 hours ago
success in developing the technologies that took on acid rain in the 1970s and mercury in the early 2000s. Program Goals The NETL Postdoctoral Research Fellowship Program (Postdoc) is a high-intensity
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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background in one or more of the following areas: dynamics analysis of power systems, machine learning, cybersecurity, renewable energy, microgrids, hands-on experiences on hardware-in-the-loop projects
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in