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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 6 hours ago
. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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approach, combining machine-learning–enhanced text-as-data analysis with qualitative discourse analysis. The project aims to produce a set of high-quality scholarly outputs, including peer-reviewed journal
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-intensive physics with nuclear/particle aspects, advanced detector R&D, machine learning and AI and emerging computational methods in quantum computing. The position is intended for an excellent and broadly
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outcomes research and real-world data analytics, with a strong publication record. Proficiency in advanced data analytics, machine learning, and statistical modeling. Job Description: The Department
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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates