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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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understanding of their molecular mechanisms remains incomplete. This project, funded by the LEO Foundation, aims to systematically characterize how skin cells respond to inflammatory signals. By integrating
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funded by the National Science Foundation. The position is focused on performance analysis and optimization of the MILC code and the libraries it calls such as QUDA or Grid. The successful applicant can
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lab focuses on the characterization of plant signaling networks that steer plant specialized metabolism within tightly regulated fitness programs, in particular those modulated by stress hormones
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. Implement Advanced Characterization Techniques to evaluate material performance and device reliability, integrating electronic control systems including DC-DC voltage boosting and maximum power point tracking
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at the Lillehei Heart Institute to study the signals that induce the maturation of myogenic progenitors derived from pluripotent stem cells (NPG Regenerative Medicine, 9:16, 2024; PNAS, 116:4346-4351, 2019; eLIFE
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Laboratory should indicate which of the LIGO sites (Caltech, MIT), if any, are preferred by the applicant, and which (if any) are likely to be unworkable. Caltech and MIT are Affirmative Action/Equal
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to relevant external sources. By enabling data interoperability across facilities and process units, this infrastructure will allow real-time coordination, intelligent scheduling, resource sharing, and improved
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and molecular phenotyping Experience with in vivo electrophysiology in rodents including device buildings, surgical procedures, freely-behaving recording procedures, signal processing and data analyses
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signal processing (GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral