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Title

Associate Research Scientist (subseasonal to seasonal (S2S) climate prediction

Posted
Reference
Sectors Including Mitigation, Science & Management
Location New York - America North
Type Fixed Term and Permanent Roles
Status Full Time
Level Mid Level
Company Name International Research Institute for Climate and Society
Contact Name
Telephone 845 680 4426
Website Further Details / Applications
International Research Institute for Climate and Society logo
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Description

The IRI invites applications for an Associate Research Scientist position in subseasonal to seasonal (S2S) climate prediction, to be located at the Lamont Campus of Columbia University. The primary responsibilities will be to develop S2S climate prediction at regional scales, including calibrated probabilistic forecast tools and products using dynamical model output from multi-model databases, and further develop IRI’s climate research on S2S scales. Topics will include identifying features/locations/episodes of enhanced S2S predictability, and prediction of user-relevant variables such as monsoon onset date. Initial focus will be over Africa and possibly Latin America. The Associate Research Scientist is expected to actively engage in the interdisciplinary research and publications as well as fund-raising activities.

Minimum Qualifications

  • Applicants must have a PhD degree in climate, atmospheric science, statistics, or related field.
  • At least 2 years of postdoctoral experience is required, as well as a strong publication record
  • The successful candidate will have experience in S2S or seasonal forecasting research using multi-model ensembles, as well as expertise in the dynamics of variability of the coupled climate system at S2S or seasonal scales.
  • Demonstrated proficiency in scientific programming languages such as Python, R or Matlab is required.
  • Excellent communications skills, both verbal and written are essential.

Preferred Qualifications

  • Experience with Python is preferred.
  • Conversational French and/or Spanish would be an advantage.
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