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integrating sensors, actuators, and control electronics. Use maker tools (e.g., CAD design and 3D printing) to prototype and refine rig components. Run daily behavioral sessions, meticulously collecting and
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support for development and operationalization of novel metadata and software solutions to manage sensor and health data for exposure health research. Projects range from metadata discovery, metadata
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outcome research, including classification, regression, clustering, and deep learning algorithms. · Statistical Software: Proficiency in statistical software such as SAS, Stata, R or Python, including
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disease. The primary focus of the lab is to elucidate how ribosomes act as sensors of cellular stress and to discover the ribosome-mediated quality control and signaling pathways that govern cell fate
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control support for ongoing clinical trials using wearable sensors, and assist with data collections during human subjects research studies as needed. The position will include collaborative interactions
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investigate (1) the role of ribosomes as critical sensors of cellular stress and (2) focus on identifying and characterizing ribosome-mediated quality control and signaling pathways that regulate cellular
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in healthy and diseased states. We broadly investigate (1) the role of ribosomes as critical sensors of cellular stress and (2) focus on identifying and characterizing ribosome-mediated quality
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to actively drive research projects to predict clinically important endpoints using your knowledge in algorithm development. You will be part of a growing, interdisciplinary team and join weekly