Position Openings - Wildfire Research

We are recruiting talented Postdoctoral Scholars (from any field) and Ph.D. Students (with an engineering background) for our NSF LEAP-HI project on wildfire simulation, risk assessment, and data analytics (read more here). The candidates will be hired through University of Nevada, Reno, University of California, Los Angeles, or University at Buffalo.

Please send me your complete C.V., if you meet the qualifications (email to hebrahimian@unr.edu).

Postdoctoral Positions

Machine Learning for Remote Sensing Applications

​Required background and qualifications:

  • Ph.D. in computer science, geography, engineering, or fields related to natural hazards

  • Extensive background in machine learning and deep learning (both theory and application)

  • Hands-on experience in remote sensing data analytics, data fusion, and multitask learning

  • Research experience and background in natural hazards - knowledge and research experience in wildfire field is a plus

  • Experience working with AWS, Google Earth Engine, and GIS data is a plus

Social Dimensions of Natural Hazards

Required background and qualifications:

  • Ph.D. in social science, geography, engineering, or fields related to natural hazards

  • Research experience and background in social dimensions of natural hazards and disaster resilience

  • Hands-on experience in qualitative research

  • Experience in data analytics and machine learning 

Ph.D. Positions

The Ph.D. candidates should have a background in engineering and willing to obtain a Ph.D. in Civil Engineering and/or Computer Science. The candidates should be good at theoretical research, solving mathematical problems, and developing and implementing large-scale computer codes. To be eligible, you should have Undergraduate GPA > 3.5 and Graduate GPA > 3.75. 

 

Machine Learning for Wildfire Data Analytics

​Required background and qualifications:

  • Background and experience in machine learning and deep learning (both theory and application)

  • An interest to get engaged with wildfire engineering field and learn new ideas related to wildfire modeling and data analytics - research experience and background in natural hazards is a plus

  • Experience developing complex applications (Python, C++)

  • Experience developing web applications (HTML, JavaScript, etc.)

  • Experience working with big data - experience with AWS, Google Earth Engine, and GIS data is a plus

  • Research experience and background in natural hazards - knowledge and research experience in wildfire field is a plus

 

Wildfire Risk and Resilience 

  • Background and experience in disaster risk and resilience 

  • Extensive knowledge in engineering probability, reliability, and risk

  • Computer programming: extensive experience with Linux, Fortran, Matlab, and/or Python

  • Experience with cloud computing and GPU-based computing is a plus 

  • Initial knowledge in machine learning and data analytics