1,026 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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postgraduate qualification in Data Science / Computer Science (PhD preferred) Strong expertise in Python and/or R, SQL, data engineering and machine learning Experience with EMR systems (Cerner highly desirable
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& Amputation Center of Excellence (EACE) is a unique organization within the Department of War (DoW) consisting of teams of researchers embedded at the point of care within multiple Military Treatment Facilities
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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a Research Fellow to contribute to a project focused on focused on data-driven discovery of atomic catalysts. Key Responsibilities: Theoretical predictions using DFT and machine learning, and
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous
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operationally safe position in real-time. This research focuses on real-time multi-objective optimization of wells, that may be achieved with a mixture of algorithmic and machine-learning approaches. Updating