Postdoctoral Associate - CEE Urban Informatics Lab & Infrastructure Resilience Group

Position Details

Recruitment/Posting

Title:

Postdoctoral Associate - CEE Urban Informatics Lab & The Infrastructure Resilience Group

Department:
Advanced Infrastructure Center

Salary: A minimum of $63,968

Offer Information:
The final salary offer may be determined by several factors, including, but not limited to, the candidate's qualifications, experience, and expertise, and availability of department or grant funds to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university's broader compensation structure. We are committed to offering competitive and flexible compensation packages to attract and retain top talent.

• Medical, prescription drug, and dental coverage
• Paid vacation, holidays, and various leave programs
• Competitive retirement benefits, including defined contribution plans and voluntary tax‑deferred savings options
• Employee and dependent educational benefits (when applicable)
• Life insurance coverage
• Employee discount programs

The Rutgers CEE Urban Informatics lab & The Infrastructure Resilience Group at Rutgers Center for Advanced Infrastructure and Transportation (CAIT) invite applications for two postdoctoral fellow positions in the general areas of community resilience, critical infrastructure protection, and smart cities.

• Lead research activities involving harnessing and synthesizing the latest developments in artificial intelligence, remote sensing, and simulation and modeling techniques in the fields of infrastructure engineering, social science, and hydrologic science to improve the resilience and security of urban environments during natural and man‑made extreme events.
• Publish conference and journal papers.
• Collaborate in multi‑disciplinary teams.
• Write grant proposals.

Minimum

Education and Experience:

Applicants must have a Ph.D. in Civil and Environmental Engineering, Industrial Engineering, Coastal Marine Science, Computer Science, Electrical Engineering, or a closely related field. Ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing; deep learning for time series data prediction; digital twin; geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems;

crowd simulation; reinforcement learning; flood modeling and impact analysis; complex system modeling; and optimization.

Required Knowledge, Skills, and Abilities:
Good communication and presentation skills, and a strong proficiency in technical writing and editing. The individual will be expected to hold very high standards in how information is developed and presented.

Quick Link to Posting: (Use the "Apply for this Job" box below)./274352

Campus:
Rutgers University-New Brunswick

Home Location Campus:
Busch (RU-New Brunswick)

City:
Piscataway

State: NJ

All offers of employment are contingent upon successful completion of all pre‑employment screenings.

Under Policy 100.3.1 Immunization Policy for Covered Individuals, if employment will commence during Flu Season, Rutgers University may require certain prospective employees to provide proof that they are vaccinated against Seasonal Influenza for the current Flu Season, unless the University has granted the individual a medical or religious exemption. Additional infection control and safety policies may apply. Prospective employees should speak with their hiring manager to determine which policies apply to the role or position for which they are applying.

Failure to provide proof of vaccination for any required vaccines or obtain a medical or religious exemption from the University will result in rescission of a candidate's offer of employment or disciplinary action up to and including termination.

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As an institution, we encourage all qualified applicants to apply. For additional information please see the Non-Discrimination Statement at the following web address: -statement