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Post-Doctoral Research Associate - Statistical Image Analysis

Job Description


Position Information
Position Information


Working Title Post-Doctoral Research Associate - Statistical Image Analysis
Department Food Science & Technology-0836
Requisition Number F_230021
Posting Open Date 02/07/2023
Application Review Date: (To ensure consideration, please submit all application materials before review date) 03/10/2023
Posting Close Date
Open Until Filled Yes
Description of Work
The Department of Food Science and Technology at the University of Nebraska-Lincoln (UNL) Institute of Agriculture and Natural Resources (IANR) is seeking applications for a highly motivated and enthusiastic post-doctoral research associate. This 12-month (calendar year), postdoc researcher appointment for the Quantitative Life Sciences Initiative will develop a nationally recognized research program in Statistical Image Analysis with specific emphasis on 3D image processing, including segmentation of 3D X-ray CT image data. Development of novel analytic methods will require advanced statistical methodology with applications to very large voxel data sets.
The successful candidate will consult with faculty, scientific experts, and other postdoctoral associates to assess what image segmentation and analyses are relevant to meet objectives, producing and demonstrating novel analyses, synthesizing findings, preparing manuscripts for publication, and presenting results at national and international conferences. Key aspects of a successful program will be the publication of high impact scientific papers and statistical software. The apportionment is 100% research. This position will be located in Lincoln, Nebraska.
Recognizing that diversity enhances creativity, innovation, impact, and a sense of belonging, the Institute of Agriculture and Natural Resources (IANR) and the Department of Food Science and Technology are committed to creating learning, research, Extension programming, and work environments that are inclusive of all forms of diversity. Consistent with the University’s N2025 Strategic Plan , we see every person and every interaction as important to our collective well-being and our ability to deliver on our mission.
As an EO/AA employer, the University of Nebraska considers qualified applicants for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See https://www.unl.edu/equity/notice-nondiscrimination .
Minimum Required Qualifications
  • PhD degree in statistics, computer science, or related discipline.
  • Experience in development of novel statistical methodology for image analysis.
  • Evidence of highly developed statistical and analytical skills.
  • Evidence of previous relevant research publications.
  • Experience with Linux, R and/or Python.
  • Excellent written and verbal communication skills.
Preferred Qualifications
  • Experience with multitype data analysis, X-ray CT imaging analysis, and interdisciplinary research.
  • Familiarity with distributed computing and high-throughput computing.
  • Record of peer-reviewed publications in statistical image analysis.
  • Strong desire to learn new skills and systems, and a willingness to adapt to change.
Pre-Placement Driving Record Review Required
Criminal History Background Check Required
Posted Salary
How to Apply
Click “Apply for this Job” and complete the information form. Attach the following documents:
  • A letter of interest that describes your qualifications for the job and anticipated contributions.
  • Your curriculum vitae.
  • Contact information for three professional references.
  • For questions or accommodations related to this position contact
    Marci Sturek
    msturek2@unl.edu
    Job Category
    Job Category (old) Post Docs & Other Academic
    Job Type 12 Month (Faculty Only)
    Position funded by grant or other form of temporary funding? No
    If Temporary, indicate end date
    Planned Hire Date
    Appointment End Date

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