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Investigator of the Martinez Zamudio laboratory, performs and assists with technical laboratory procedures and computational analysis of ongoing research projects focusing on the function of transcription factor
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) to address business questions and improve business outcomes. The BI developer partners with various IT personnel and stakeholders in identifying required data elements. The developer has knowledge of data
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evolutionary biology. The postdoctoral associate will develop and benchmark methods for evolutionary analysis by the comparison of protein structures, conduct rigorous evaluations of the concordance
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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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resources; project specific data analysis and reporting; and, responding to requests for information. Among the key duties of this position are the following: Develops training modules and materials related
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materials, and surface analysis methods. Key Duties & Responsibilities 1) Metal nitride synthesis – 25% 2) Reaction product characterization- 25% 3) Set up, fix, and operate equipment- 20% 4) Writing journal
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computational analysis of ongoing research projects focusing on the function of transcription factor (TF) networks in mediating cell fate transitions at the early stages of oncogenic transformation as
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research on characterizing non-coding regulatory elements in humans and understanding how these elements change across different conditions. The project will involve developing new modeling approaches
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departments and stakeholders to identify appropriate data elements and analytics tools to address institutional questions and communicate results to multiple audiences using various means. Adapts quickly
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research staff in data analysis and relevant research projects as assigned by the Principal Investigators. May assist with the coordination and evaluation of non-professional staff training. Conducts data