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Field
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Assistant under the supervision of Prof. Antonio J. Gil, in order to meet the research objectives of an awarded Research Fellowship in the area of control modelling of EAP driven soft robotics. Specifically
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simulation models of existing test structure geometries to enable simulation and optimization for specific PIC platforms Investigate methods to optimize test structure designs for more robust determination of
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’ methodological skillsets. There are different models of Postdoctoral programs. CIL follows the Academic Community model, whereby fellows are part of an academic community learning and advancing not only from
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. Proficiency in programming languages such as Python, C++, and MATLAB for spacecraft modeling and simulation. Experience with simulation environments and tools used in space research (e.g., GMAT, STK, Gazebo
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. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
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propose strategies for fields on the Norwegian continental shelf. Competence required in at least one of the following fields: Reservoir simulation, computational modelling Competence desired: Subsurface
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for modeling unprecedented electromagnetic phenomena, using languages such as C++ and Python. Formulate new theories pertaining to EUV generation, obtained ab initio from Maxwell’s equations and quantum
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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members, and the public. Unit URL https://www.uidaho.edu/engr/research/csds https://www.idahoepscor.org/ Position Qualifications Required Experience Experience in using power system modeling and simulation
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal