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Field
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, optogenetic and electrical stimulation, neuromodulation and lesion-based validation, signal processing, computational network analysis, and dissemination of results. The postdoctoral associate will work with
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placed on multi-omics data integration, statistical modeling, biomarker discovery, pathway/network analysis, and development of reproducible computational workflows. This position provides an excellent
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, or chaotic neural networks. Experience with network dynamics. Experience with time-series analysis. Experience with stochastic processes. Experience with computational modeling of biological systems
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 10 hours ago
Posting Description POSTDOCTORAL ASSOCIATE, Center for Sustainability Science & Strategy, to join an international team of scientists working as part of the global AGAGE network and a large
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an interdisciplinary team. Your tasks Conduct physical vapor deposition experiments using advanced PVD processes such as synchronized HiPIMS Perform in-depth materials characterization and surface analysis Apply and
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pavement networks. This position will focus on modeling and optimizing pavement performance under evolving climate and hazard conditions. This position will advance modeling of pavement life-cycle
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funded NIH R01 project dissecting the SOX4/SOX9 transcriptional regulatory network that governs biliary development in Alagille syndrome and advancing the therapeutic potential of targeting this network in
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research agenda leading to production of research articles, project reports, analysis reports, and other outputs related to two projects. NY SMART I-Corridor – As an official awardee of the New York
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, particularly gene-regulatory network inference, pathway analysis, or inferred protein-activity analysis. ChIP-seq, viral vector methods, genome engineering, or related molecular approaches. Candidates are not
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Conduct physical vapor deposition experiments using advanced PVD processes such as synchronized HiPIMS Perform in-depth materials characterization and surface analysis Apply and improve high-throughput