15 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" positions at University of Washington
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figures of lab members. Candidate will train on the lab’s fundamental algorithms and run them in a collaborative manner with other team members to generate paper figures and make discoveries. Collaborative
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figures of lab members. Candidate will train on the lab’s fundamental algorithms and run them in a collaborative manner with other team members to generate paper figures and make discoveries. Collaborative
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electrode arrays - 20% data analysis with advanced methods such as multiple regression, fourier domain algorithms, modern statistical approaches - 5% paper preparation including writing text, making figures
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new code in python at PEP8 standards for solving problems toward creating neural connectome maps). Algorithm development initially will involve solving problems such as: (1) base calling of in situ
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scientist, the Research Scientist/Engineer 4 (RS/E 4) will apply data mining techniques, perform statistical analysis, develop visualization techniques, and build automated tools that can assist with
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competency, and QA/QI. Oversee and consult in development of optimized laboratory utilization algorithms. Consult and collaborate with existing clinical research units to support ongoing laboratory projects
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either back-end Java development, front-end UI development, and/or signal processing algorithm development. This position will work on all phases of software application development ranging from
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projects. Desired: Doctoral Degree in Bioengineering, immunology, systems biology Experience using open source packages and adapting or developing new algorithms to analyze single-cell transcriptomics and
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collaborative projects with other lab members and developing experimental protocols and experimental cell and molecular biology standards for the laboratory. The scientist will work on projects broadly
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postdoctoral scholars, working on the development of a core, scalable methodology. This methodology leverages existing spatial data on landscapes, fire behavior, and fuel treatments to evaluate real-world