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machine learning algorithms for extracting movement and contextual data from multimodal sources including videos, biosensor recordings, and text. Job Description Job Responsibilities Perform data annotation
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from specialized human movement datasets. Assist in identifying available datasets, performing data annotation, developing and applying machine learning algorithms for extracting movement and contextual
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel
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control, and related topics. The position requires expertise in the design and assessment of new protocols and algorithms, establishing their correctness, and overseeing lab personnel who experimentally
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implementation of smartphone/tablet-based applications and wearable sensor systems to measure neurologic symptoms), and analyzing resulting data. This role provides an opportunity to work at the intersection
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experts, and translate them into efficient and maintainable code. This requires knowledge in (or the ability to learn) macroeconomics, a good foundation in (optimization) algorithms, and the ability
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to learn) macroeconomics, a good foundation in (optimization) algorithms, and the ability to effectively parallelize code, in addition to proficiency in Python and general software engineering skills
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. Learn to follow proper safety practices. Use diagnostic equipment such as a resistance drill, soil moisture sensors and sampling techniques. Contribute to the Arboretum blog on topics relevant to current
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responsibilities include, but are not limited to, the following: Lead the design, development, implementation, testing, deployment, documentation, and maintenance of machine learning algorithms, applications
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. Experience with data wrangling and analytics in R Good understanding of data structures and algorithms Ability to communicate clearly and concisely, including written documentation and data visualization