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The postdoctoral scholar is responsible for independent and collaborative development, implementation, and analysis of scientific research in the discipline of clinical informatics and digital imaging activities, including data analysis and statistical pattern recognition, outcomes analysis and predictive modeling to answer clinical questions in laboratory medicine including questions related to resource utilization and new diagnostic modalities and technical strategies and methods for implementing date integration and decision support. The scholar will utilize principles and approaches from information sciences, data management, software architecture, statistics and data mining. Responsibilities include management of all aspects of planning and performing scientific investigations and analysis on clinical data sets with guidance from departmental faculty. Duties include: hypothesis development, literature review, collection of pilot data, report writing, and supervising of undergraduate research students and graduate research students, overseeing data collection procedures, supervising experimental procedures, review of data for quality control, supervision of data entry/data analysis, analysis of research hypothesis using descriptive and multivariate statistics, and the development of independent and collaborative presentations and publications. Scholars are expected to demonstrate compliance with established guidelines and regulatory standards for research including biosafety, responsible conduct of research and human subjects training.
Approximately 80% of the postdoctoral scholar's time will be devoted to informatics.
Approximately 20% of the postdoctoral scholar's time will be devoted to managing the day-to-day activity of undergraduate and graduate research students in the laboratory.
Experience in computer science with a strong computational background and interest in programming, database management, hospital and laboratory information systems and electronic health records, and state-of-the-art software tools. Strong written and verbal communication skills, high-level programming skills in C/C ++, Fortran, and/or Matlab/Mathematica, knowledge or research experience with multiscale modeling and data mining and analysis.
Qualifying degrees should be received from appropriately accredited institutions.
Excellent written and oral communication skills.