• VePub Press

Vermont EPSCoR is recruiting a research assistant professor with expertise in machine learning and complex systems modeling to join our NSF-funded research on Basin Resilience to Extreme Events (BREE). We are in the second year of a large five-year interdisciplinary project which seeks to understand how the Lake Champlain Basin’s landscape, watershed and lake conditions respond to extreme weather events. The work will test policy scenarios for enhancing resilience using our comprehensive Integrated Assessment Model (IAM). As a member of the BREE team, the successful applicant will participate in unique learning and professional development experiences including learning to communicate science through our program with the Alan Alda Center for Communicating Science, and will have access to significant cyberinfrastructure including a programming team and local and national computational resources.

Qualifications:

  • A PhD (or equivalent) in computer engineering, computer science, systems engineering or a related field
  • The demonstrated ability to model social and/or natural systems with an emphasis on embedding machine learning and complex systems methodologies in the models
  • Experience in the use of deep learning network frameworks (e.g. Tensorflow) to explore decision-making machine learning challenges such as those that might be used to drive agent behavior in an agent-based model
  • Experience in complex systems analysis including multi-objective optimization and the quantification of uncertainty as it propagates through a complex system
  • The ability to work effectively on a large, interdisciplinary team and contribute to the integration of work into a larger modeling framework

This research position will be funded for two years. Intended start date is ASAP and applications will be reviewed as they are received.

To apply: Please send your CV and a cover letter outlining research interests, expertise and availability to epscor@uvm.edu.


  • The University of Vermont and State Agricultural College is committed to a policy of equal employment opportunity and to a program of affirmative action in order to fulfill that policy. The University will accordingly recruit and hire into all positions the most qualified persons in light of job-related requirements, and applicants and employees shall be treated in employment matters without regard to unlawful criteria including race, color, religion, ancestry, national origin, place of birth, sex, sexual orientation, disability, age, positive HIV-related blood test results, genetic information, gender identity or expression, or status as a disabled veteran, recently separated veteran, other protected veteran or Armed Forces service medal veteran, as these terms are defined under applicable law, or any other factor or characteristic protected by law.



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