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Field
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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motivated Post-Doctoral Associate to join our team with a strong background in robot control, machine learning, and differential geometry to work on the development of advanced algorithms to enhance
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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Intelligence (AI) and Mathematics. This position involves applying machine learning tools, particularly reinforcement learning (RL), to address complex research-level mathematical problems and developing new
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on the hiring manager’s preferences and should include things that can be learned or trained for. Preferred Schedule: Monday - Friday 8:00-5:00 Position Requirements: Specifications Appropriate experience may be
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/Credentials/Licenses N/A Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned vehicles No Does
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score derivation and validation, and other relevant analyses. Develops R or Python scripts for data analysis, statistical modeling, and machine learning techniques, ensuring reproducibility and efficiency
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, excellent communication skills, excellent computer literacy. Certifications/Licenses Required Knowledge, Skills, and Abilities PhD in life sciences. Experience with proteomics, bioinformatics, mass
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. Demonstrated expertise in interdisciplinary research with technical and clinical teams and patients desired. Experience leveraging machine learning for human musculoskeletal biomechanics applications desired