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Field
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, and/or automation. Demonstrated track record of peer-reviewed publications in areas such as computer vision, robotics, automation, and/or embedded control systems, particularly with applications in
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management, collection & visualization Social network analysis & graph theory Online tool/web development Running controlled experiments Game-theoretic modelling Excellent communication skills in English
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. The candidate should have a strong background in process modeling, control, optimization, applied machine learning, and AI. City: Cranbury State: NJ Location: Off Campus Create a Job Match for Similar Jobs About
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time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process, organize, interpret, review
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 8 days ago
the physical process understanding of hydrometeorological processes. This includes physical processes such as streamflow, evapotranspiration, and interactions with other earth systems such as the atmosphere
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of termination, with a major focus on quality control processes, including mRNA surveillance and ribosome-associated quality control. Required qualifications include a Ph.D. in Molecular Biology/Molecular
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
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or projects under control or supervisory responsibility. 2. Recommends changes in research, testing or experimental procedures. 3. May be responsible for a single highly technical and complex piece of research
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surveillance, prevention, and control of infectious diseases. Example projects include assessing drivers of global infectious disease dynamics and developing short- and long-term forecasts for those diseases