Deep-Learning Postdoctoral or Faculty Researcher

Vermont EPSCoR
University of Vermont (UVM) in Burlington, VT
Competitive salary and benefits
March 16 2017
Position Type
Full Time
Organization Type

Deep-Learning Postdoctoral or Faculty Researcher (Position ID: PDA#005)

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


  • A PhD (or equivalent) in computer engineering, computer science, systems engineering or a related field
  • The demonstrated ability to model physical (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 their work into a larger modeling framework

This research position will be funded through May 2019.  Intended start date is June 1, 2017.

To apply:  Please send your CV and a cover letter outlining research interests, expertise and availability to and reference Position ID PDA#005.

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