11 developer-"https:"-"https:"-"https:"-"Univ" research jobs at University of Central Florida
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development of research proposals and reports, manage sponsored research projects, supervise graduate research assistants, represent the DISCOVER Lab at national and international conferences, symposia, and
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. Responsibilities will be both independent and collaborative, with an emphasis on career development, scholarly productivity, and the application of implementation science methods to real-world public health
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milestones, coordinate and attend team meetings and contribute to annual reports, train and facilitate the management of team members, lead and contribute to scholarly writing, and conduct research with
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will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications. Job
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prediction of combustion dynamics and emissions in next-generation gas turbine combustion systems operating with gaseous and liquid fuels. • Develop, implement, and validate CFD models for complex reacting
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proteomics while developing expertise for independent work. Responsibilities: Conduct research aimed at profiling proteome changes in cancerous environments, during process of regeneration and/or in response
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/maintenance, the collective supervision of graduate and undergraduate students, and dedicated activities related to professional development. Responsibilities: Research: Conduct advanced research in
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electrochemical and physicochemical data. Prepare progress reports, technical documentation, and research papers. Assist in writing proposals, manuscripts, and patents. Supervise and mentor graduate/undergraduate
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with members from three universities, one clean energy start-up company, and a DOE national laboratory (Sandia) for a prototype reactor development and demonstration. The scholar will also help Dr. Li
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responsibly. What You’ll Work On You will contribute to the development and evaluation of ethics-centered adaptive brain/muscle–machine interface technologies using physiological signals (primarily sEMG