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, including participant recruitment and data collection. Support data analysis (experience analyzing longitudinal data preferred) and co-author peer-reviewed manuscripts. Contribute to grant development and
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, 7nAChR, 9* nAChR, GIRK1/2, GIRK1/4, etc.) Conducting biochemical and ADME/PK studies and data analysis Generating SAR hypotheses Performing empirical and structure-based target design Executing synthetic
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biochemical and ADME/PK studies and data analysis Generating SAR hypotheses Performing empirical and structure-based target design Executing synthetic chemistry and troubleshooting Improving the potency
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associated regulatory interactions Real-world evidence generation and analysis to identify unmet needs and inform comparative effectiveness, global epidemiology (including race, ethnicity, age, sex) to support
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the Institute for Mechanobiology (IfM) in Boston, MA (see https://mechanobiology.northeastern.edu/our-faculty for list of the IfM core faculty). This position has an initial 2-year appointment, renewable
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, a7nAChR, a9* nAChR, GIRK1/2, GIRK1/4etc.). Key initial responsibilities will include biochemical and ADME/PK studies and data analysis, SAR hypothesis generation, empirical and structure-based target design
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with other faculty and researchers of the Center. Responsibilities: This postdoctoral position will involve leading independent research, as well as conducting analysis of existing data, which can range
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applications of neural networks to the analysis of multi-omic data, models for predicting phenotypes using genotype data, biological data integration, etc.. Participation in these projects will include
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. Responsibilities The fellow will play a collaborative and leadership role in project design, study implementation, analysis, survey construction, data collection, data analyses, preparation of publications and
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. Through hands-on experience, fellows will work with various cross-functional teams to learn the role of Medical Affairs, develop skills in the analysis, interpretation, and communication of clinical data