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Field
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David Levinson , the successful candidate will contribute to the development of hybrid quantum-classical modelling approaches that support improved analysis, simulation, optimisation, and decision making
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to autonomous systems is considered an asset. Proficiency in relevant programming and simulation tools, such as Python, C/C++, MATLAB/Simulink, ROS/ROS 2, Gazebo, AirSim, or equivalent platforms. Experience in
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device performance Support device simulation and optimization using TCAD tools Demonstrate the proof-of-concept of novel FDSOI device technologies and support their transfer to a startup for further
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candidate. A CV that includes a list of publications. A copy of the doctoral degree certificate, and other certificates or grades you wish to be considered. Contact information for two references. Incomplete
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experience, proposed contribution to the project, support needs, and any additional relevant information; an academic recommendation letter; a copy of the PhD diploma; and a CV in the FAPESP format or similar
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to investigate and develop novel ceramic electrolytes for next-generation composite solid-state batteries. Particularly halides and sulfides are of interest. By integrating atomistic simulations with experimental
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motivation for applying for the position. · Curriculum vitae (CV) with publication list (including a brief description of the applicant’s contribution to each publication). · Verified copy
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Research Associate, Chemistry & Biochemistry Posting Number req26544 Department Chemistry & Biochemistry - Sci Department Website Link https://cbc.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA
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Responsibilities work on the research projects related to photonic or neutral atom quantum computing, and quantum information/simulation under co-supervision of Profs. Zidan Wang & Xianmin Jin coordinate theoretical
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (www.foylab.xyz/) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving