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Job ID: 191718

Postdoctoral Associate - Digital Twin Modeling of Civil Infrastructure
University of Pittsburgh


Date Posted Aug. 4, 2022
Title Postdoctoral Associate - Digital Twin Modeling of Civil Infrastructure
University University of Pittsburgh
Pittsburgh, PA, United States
Department Civil and Environmental Engineering
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Post-Doc
  • Structural Engineering
    Mechanical Engineering
    Engineering Mechanics
    Civil Engineering
 
 

Job Description

The Department of Civil and Environmental Engineering is inviting a motivated Postdoctoral Associate to join the DISCOVER (Digital-Twin Infrastructure Science for Operations in Virtual and Extended Realities) Laboratory and become part of an interdisciplinary research team conducting research at the convergence of computational mechanics, civil infrastructure resilience and digital twin modeling. The position will require extensive collaboration across disciplines to tackle research that incorporates engineering mechanics, data science, and remote sensing. The candidate will assist the DISCOVER lab with managing existing research projects and preparing research proposals and publications in the research areas listed above.

Responsibilities

The Postdoctoral Associate will lead the 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 professional meetings through published research works and presentations. The selected candidate will have an opportunity to work in a research-oriented laboratory equipped with state-of-the-art hardware and software tools, performing cutting-edge research related to digital twin modeling of large-scale infrastructure systems. The position is perfect for recently graduated post-doctorate professionals looking to grow their research records (with additional, optional opportunities to grow their teaching portfolio, according to the candidate’s preference). However, other more-experienced candidates will also be given consideration.

Minimum Qualifications:

  • PhD in Civil Engineering, Mechanical Engineering, or related field.
  • Excellent written and oral communication skills.
  • Potential to lead the development of research proposals and grants.
  • Demonstrated leadership/managerial and organizational skills.
  • Full professional proficiency in one of the following languages: Python (including PyTorch and TensorFlow), Julia (including Flux and CUDA), Matlab.

Preferred Qualifications:

  • Experience in the development of computational mechanics applications in one of the aforementioned programming languages.
  • Experience with data acquisition, pre- and post-processing for civil infrastructure Structural Health Monitoring.
  • Unmanned Aerial Vehicle (UAV) piloting experience (CF Part 107 license is a plus

Application Details

Start Date: as soon as possible, no later than January 2023.

Contract Duration: initial appointment will be for 12 to 18 months (with potential to extend, depending on available funding and performance).

Primary Advisor: Dr. Alessandro Fascetti (fascetti AT pitt DOT edu).

Applications should include: (i) a cover letter, (ii) detailed Curriculum Vitae, (iii) a short (1-2 pages) research statement, and (iv) contact details for at least two references. Review of applications will begin immediately. Shortlisted candidates will be invited for online interviews.

For further information or questions about this position you may contact: Dr. Alessandro Fascetti (fascetti AT pitt DOT edu). Applications are being accepted at join.pitt.edu, Job Number: 22006049.


  • The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EOE, including disability/vets The University of Pittsburgh requires all Pitt constituents (employees and students) on all campuses to be vaccinated against COVID-19 or have an approved exemption. Visit coronavirus.pitt.edu to learn more about this requirement.


 
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