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of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a significant computational component in deploying multi-GPU codes
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(FOPH) of Switzerland and the Centers for Disease Control and Prevention (CDC) of the United States. We value good software engineering practices. We perform code reviews, have automated testing pipelines
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mechatronics systems is a plus Excellent coding skills in python, ROS, and RL&IL pipeline experience on simulator and training libraries. Knowledge on C++ is a plus Experience with Physics simulators such as
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) Unsupervised machine learning and deep learning methods Analysis, visualization, and interpretation of learned design spaces Contributing to research outputs (prototypes, publications, open-source code) Profile
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development, validation, and safe integration of locally hosted LLMs for automated coding of pediatric diagnoses from electronic health records (EHRs), with the goal of enhancing research capabilities and
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community Contribute to R data publication packages washr and fairenough Profile You care about data and code being concise and easily reusable You know how to use standard data science tools (Git, GitHub, R
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programming skills (ideally Python) and commitment to clear, reproducible, well-structured code Working knowledge of SQL and/or NoSQL databases (and motivation to deepen your expertise) Strong analytical
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disseminated through open-source code and scientific publications. Start: As soon as possible (applications reviewed on a rolling basis) Duration: 6 months (extendable) Job description Apply computational and
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(e.g., qualitative coding, statistics, simulation, ML) Publish results in peer-reviewed venues (conferences/journals) and contribute to paper writing Support lab operations as needed (maintaining
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seamlessly into code Contribute to brand identity: logo development, visual guidelines, style systems Profile Degree in Interaction Design, Visual Communication, Graphic Design, or related field Background as