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Field
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multidisciplinary research team are required 7. Knowledge of artificial intelligence (AI) models and development of AI tools with applications in disease detection/diagnosis and epidemiology is desirable 8
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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Location: Cambridge, Massachusetts 02142, United States of America [map ] Subject Areas: Artificial Intelligence Biology Machine Learning Appl Deadline: (posted 2024/09/30, listed until 2025/09/30) Position
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engineering tools, including process modeling, process control, machine learning, and artificial intelligence, to support ongoing proposal efforts in advanced pharmaceutical manufacturing. The successful
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NSF, FEMA, DHS, and other local agencies. They will lead research activities involving harnessing and synthesizing the latest developments in artificial intelligence, remote sensing, and simulation and
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candidate will work collaboratively with a team of scientists from the Artificial Photosynthesis (AP) and Catalysis: Reactivity and Structure (CRS) groups and will be supervised by CHASE principal
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Focus – design and development of engineered and artificial enzymes for biocatalysis and asymmetric synthesis Projects – involve biocatalysis, protein engineering/directed evolution/design, and
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-motivated person to lead OME initiatives designed to advance knowledge of the role of advanced data systems (e.g. Artificial Intelligence (AI), Virtual Reality (VR)) in public health applications and
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professional deliverables ● Experience with causal inference, machine learning, and artificial intelligence is desirable ● Experience with clinical, EHR, or biobank data analyses is desirable
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wildfire simulation, fuel modeling, remote sensing, data-driven methods, artificial intelligence, and real-time applications. The successful candidates will contribute to the development of faster than real