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-reviewed journals and conferences Demonstrated research experience with HPC, AI/ML and/or distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as
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analysis skills using Python, MATLAB, or similar platforms. Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and to participate creatively in
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following areas: automated controls, SLAM, autonomous navigation, or trajectory planning. Experience integrating hardware, deploying, and evaluating algorithms on physical robots. Proficiency in Python
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data
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Experience with numerical computing using programming languages such as C++, Python, etc Author or co-author of open literature publications Special Requirements: Applicants cannot have received their Ph.D
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analysis, modeling, or automation using tools such as Python, MATLAB, C#, C++, or similar engineering software environments. Experience with CAD/CAM/CAE tools such as Siemens NX, SolidWorks, Mastercam
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knowledge of models of strongly correlated electron systems Proficiency with scripting or programmatic languages, such as Python, c, and matlab Excellent written and oral communication skills Motivated self
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data acquisition, data analytics, statistical modeling, and machine learning in manufacturing environment. Proficiency in Python and common data science and machine learning libraries (e.g., NumPy
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Qualifications: A Ph.D. degree in electrical engineering, or related discipline completed within the last five years. Expertise in power systems and power electronics. Experience in C/C++, Matlab, and Python
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Requirements: The prospective candidate should be well-versed with deep neural networks, have experience working on PyTorch or similar DL frameworks, programming in Python (preferred), NLP packages and pipelines