The successful candidate will work with SCRiM researchers and collaborators across multiple transdisciplinary projects to develop customized climate data products for climate impacts studies and decision support applications. These efforts will focus on the use of empirical/statistical downscaling and data-model fusion techniques to generate localized climate data sets that capture the broad range of structural, parametric, forcing, and spatio-temporal uncertainties identified as relevant for particular applications, including agriculture, forestry, transportation, and coastal infrastructure. Scholars with interests and/or experience in climate modeling, dynamical downscaling, uncertainty quantification, and data assimilation are also encouraged to apply.

For more information, please contact Dr. Robert Nicholas ( To apply, visit