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teaching load of 1-1. Successful candidates may come from any area in the humanities, with research and teaching complementing our program’s interdisciplinary educational mission. Working knowledge in
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teaching load of 1-1. Successful candidates may come from any area in the humanities, with research and teaching complementing our program’s interdisciplinary educational mission. Working knowledge in
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: Bibliography and identification of the energy system components. Theoretical modeling and simulation of the flow systems. Data analysis. Assisting the PI and the sponsor in grant writing for other funding
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Mechanical, Aerospace or Electrical Engineering, or other related fields specializing in the area of machine learning and dynamical modeling, excellent problem-solving skills as well as good oral and written
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using real-time monitoring systems. Develop AI and machine learning models to integrate real-time monitoring data Collaborate with colleagues in computer science and computer engineering to integrate
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: Product design and improvement, exploring larger scale manufacturing. Theoretical modeling and simulation of the biomimetic system. Data analysis. Assisting the PI and the sponsor in grant writing for other
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models, and empirically test those models with integrated and fused data. Development of data-serving APIs is also part of the work plan and duties for the candidate. The candidate will play a vital role
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from apparatus and systems Create simulation models and perform simulation of test apparatus and cooling devices and systems using commercial software Participate in weekly meetings and help to prepare
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, the individual will work with existing field, laboratory, and model projects to execute new methods and analysis. Minimum Qualifications: The successful candidate must have: a Ph.D. degree in water resources
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from apparatus and systems Create simulation models and perform simulation of test apparatus and cooling devices and systems using commercial software Participate in weekly meetings and help to prepare