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, Computational Engineering Science, Chemical Engineering or a comparable course of study Previous experience with programming in Python Experience in modeling, simulation or machine learning Fluent / good
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well as the accomplished research project BOTTOMS-UP. Depending on your skills and preferences, Artificial Intelligence (Machine Learning) can be used for predicting aspects of forest biodiversity based on existing as
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, developing, and implementing innovative machine learning models and algorithms to drive insights from the hEDS*omics multimodal dataset, encompassing clinical, environmental, and multi-omics data. This role
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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 23 days ago
/Administrative Internal Number: 25191 MACHINE LEARNING ENGINEER, Jameel Clinic for Machine Learning, will lead deploying machine learning models developed in our labs; collaborate with researchers to improve novel
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Credits): Learn to use Computer Integrated Manufacturing to create three-dimensional models of mechanical parts: Computer Aided Design (CAD) digital modeling into Computer Assisted Manufacturing (CAM
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graduate researchers Cultivate a collaborative learning environment across the lab AI-Driven Mechanistic Discovery (40%) Help develop and train a “Street Lab AI model” to generate and test quantitative
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. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques Preferred: Prior working experience with EHR data, machine
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical