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  • Postdoctoral Fellow
    Industrial Engineering or Statistics
    University of PIttsburgh

    A postdoctoral Scholar position for a statistician/data scientist is available in MDS-Rely (http://mds-rely.org), a National Science Foundation Industry University Cooperative Research Center at the University of Pittsburgh under the direction of Prof. Paul W. Leu (Industrial Engineering, http://lamp.pitt.edu) and Satish Iyengar (Statistics). The research focuses on using data analytics to understand and predict materials degradation and lifetime performance of materials and systems. Combining time series, spectral and image data is necessary. The real-world data comes from Laser Powder Bed Fusion based Additive Manufacturing and Electromagnetic Interference Shielding.

    The Postdoctoral Scholar will be responsible for original and collaborative research, related data analysis, software development and publications, as well as some student supervision and coordination of studies. This position holds excellent career development opportunities through participation in the center and regular interaction with industrial and government lab members of MDS-Rely. Preference will be given to individuals with experience in real-world data analytics and a demonstrated ability to lead a project, collaborate with domain scientists, analyze data, and write manuscripts.

    The applicant should hold a Ph.D. degree in Statistics, Biostatistics, Computer and Data Sciences, Materials Science or a related field. Excellent analytical and computing skills in R and/or Python are required and familiarity with Hadoop/Hbase/Spark would be helpful. Experience with Linux is a plus. Strong oral and written communication skills and ability to work independently and collaboratively are essential. The applicant should be familiar with the linear modeling, fixed effects and mixed/random effects modeling, logistic regression, predictive modeling, and cross-correlation of data sets. The research scholar will lead and mentor students in R/Python code development and data analysis of large and diverse data sets in a Hadoop/Hbase distributed computing environment, including time series and point in time data. The applicant will utilize Agile Software Development Practices, including design, modeling, coding, testing, planning, risk management, process, quality, etc and will utilize Agile Tools including Bitbucket, Git, Confluence, Jira and Slack following a Kanban framework. Codes developed will be provided to Center Members as packaged based systems with well-developed, open source codes..

    Applicants should send a cover letter including a brief description of research experience and interests, a curriculum vitae, and contact information for at least three references by email to pleu@pitt.edu with the subject line: MDS-Rely Postdoc Application.

 


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