48 software-defined-networking Postdoctoral research jobs at University of Washington
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learning from computer science or related areas and be proficient in Java, C, and Python programming. Familiarity with the source code of major open source machine learning software packages such as Weka
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Relations website at https://hr.uw.edu/labor Qualifications University of Washington postdoctoral scholar appointments are for a temporary, defined period not to exceed five years/60 months, including any
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junior PI, I am committed to providing personalized mentorship and supporting your career development through active guidance, networking, and publication opportunities. Our research integrates
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variety of experimental data, utilize different model structures/modeling techniques, are often closed source or coded in proprietary software packages with poor interoperability, and process experimental
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synthesis, dynamic covalent chemistry, catalysis, and additive manufacturing are encouraged to apply. University of Washington postdoctoral scholar appointments are for a temporary, defined period not to
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tumor progression. Specifically, we investigate how transcriptional regulators and gene networks govern immune and brain cell behavior. Our lab uses a broad array of approaches, including flow cytometry
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, to define novel biomarkers, and to identify novel therapeutical targets. We have pioneered in the integration of genetics with omic data to identify proteomic signatures and develop novel predictive models
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skills, including writing, public speaking, networking, and critical evaluation of scientific literature. Presents scientific work both inside and outside the University with excellent oral communication
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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs
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on extreme heat. Under the mentorship of the PI Dr. Karen Chen, the postdoc will collaborate with the MedRIN network to disseminate findings enhancing innovation, rigor, and open access for scientific