Post Doctoral Associate - MDS Rely

University of Pittsburgh; Pittsburgh (Allegheny County); On-site; USD 55,000 - 75,000; Full time

Job summary

The University of Pittsburgh invites applications for a Postdoctoral Associate in MDS Rely Industrial Engineering. The role focuses on statistics, data science, and analyzing materials degradation using time series, spectral and image data from real-world additive manufacturing sources.

You will lead and collaborate on research, perform data analysis and software development, supervise students, and help publish manuscripts.

Qualifications

• Ph.D. in Statistics, Biostatistics, Computer and Data Sciences, or Materials Science.
• Strong experience with R and Python for data analytics.
• Familiarity with Hadoop/HBase/Spark is preferred.

Responsibilities

• Lead original and collaborative research projects in MDS-Rely.
• Perform data analysis and software development.
• Publish findings and mentor students.
• Coordinate studies and present results to center members.

Skills

R

Python

Time series analysis

Data analysis

Manuscript writing

Education

Ph.D. in Statistics/Biostatistics/Computer and Data Sciences/Materials Science

Tools

Hadoop/HBase/Spark

Linux

Git

Bitbucket

Confluence

Jira

Slack

Job description

Post Doctoral Associate - MDS Rely Industrial Engineering - Pennsylvania-Pittsburgh (26006341)

A postdoctoral Associate 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 the 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 Associate 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 the ability to work independently and collaboratively are essential. The applicant should be familiar with 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.

The University of Pittsburgh is an equal opportunity employer / disability / veteran.

Assignment Category: Full-time regular

Campus: Pittsburgh

Child Protection Clearances: Not Applicable

Required Attachments: Cover Letter, Curriculum Vitae

Equal employment opportunity, including veterans and individuals with disabilities.

PI287633009