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(i.e. machine learning, neural nets, LLMs). Prepare results and design figures for reports and presentations. Manage and manipulate data using requested languages, including Python, R, MATLAB, and STATA
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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. Qualifications Essential Requirements Three (3) years minimum field experience with utility, industrial power plant operations, or military in the electrical field. Ability to read and understand electrical
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circuit package assemblies. Perform epoxy die attachment using semi-automatic die placement machines. Conduct wedge and ball bonding using semi-automated wire bonding machines. Ensure precise alignment and
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research associate positions broadly in statistics and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu ). The position is for one year with the possibility of reappointment
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, synthesize, and analyze data. Produce empirical analysis and more sophisticated statistical models (i.e. machine learning, neural nets, LLMs). Prepare results and design figures for reports and presentations
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Master's degree in Computer Science, Computational Science, Engineering, Mathematics, or a related field or post-doctoral candidate. Experience with machine learning techniques and their integration
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Laboratory for Artificial Intelligence (the AI Lab) and will receive a competitive salary, benefits, office and equipment, computer resources, and yearly research support. Appointments are for one year with
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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the ability to learn computer basics. Must be capable of working with others on a team, yet be able to take on responsibility and function independently. Must be an organized, self starter who is capable