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Field
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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highly motivated researchers in all areas of the field, including but not limited to: quantum algorithms and complexity; quantum information theory; quantum cryptography; quantum information in many-body
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will have a strong background in wireless communication, signal processing, and machine learning. They should also possess the skills necessary to develop complex models, algorithms, and simulations
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(NLP) algorithms applied to electronic health records (EHR) to understand cannabis-related harms in aging PWH and people without HIV. The position will entail collaborations with several investigators
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data analytics, and manufacturing process optimization. Develop and apply models, algorithms, or data analysis workflows to support machining process understanding, machine tool characterization, process
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expanding the Food Compass algorithm according to the latest science, including expansion to include novel health-related bioactive attributes; Supporting ongoing work and manuscripts, including related data
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ultrasound technologies, ultrasound-responsive drug carrier formulations, and adaptive closed-loop control algorithms as an integrated precision drug delivery platform for the brain. Our approach employs a
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languages like Python or C, and or developing and/or using computational methods for analyzing large datasets. Demonstrated experience in developing computational algorithms for solving problems, preferably
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
developing novel methods and algorithms for applications in the Engineering Design domain; demonstrating a commitment to deliver results; working on research proposals; and working in a team environment. Job
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simulations and data analysis. This includes data analysis using Python-based algorithms. Experience with EELS is preferred. Skills This See Experience