Postdoctoral Researcher: Ocean ML for Climate Insights

Research Foundation Cuny; New York (NY); On-site; USD 75,000 - 82,000; Full time

Benefits offered by this job

Annual travel budget of $8,000

Budget for computer supplies and publication support

Job summary

A leading educational foundation in Brooklyn, NY, is seeking a Postdoctoral Researcher to enhance machine learning modeling in climate science. Candidates should have a Ph.D. in a relevant field, strong Python programming skills, and experience with statistical modeling. This full-time role offers a starting salary of $75,000-$82,000 and opportunities for professional development in a collaborative research environment. Successful applicants will work on critical climate data projects with interdisciplinary teams.

Qualifications

• Ph.D. required, ABD considered but must graduate before start date.
• Strong motivation and genuine interest in Climate Data Science.
• Demonstrated collaborative mindset and interdisciplinary interest.

Responsibilities

• Improve ML modeling and enhance generalization strategies.
• Conduct generalization tests using Earth System Models.
• Develop and assess custom metrics for feature variable relationships.

Skills

Strong programming experience in Python

Advanced mathematical modeling and statistical modeling skills

Familiarity with Machine Learning algorithms

Excellent mastery of written and spoken English

Education

Ph.D. in physical or mathematical sciences

Climate science or closely related discipline

Job description

A leading educational foundation in Brooklyn, NY, is seeking a Postdoctoral Researcher to enhance machine learning modeling in climate science. Candidates should have a Ph.D. in a relevant field, strong Python programming skills, and experience with statistical modeling. This full-time role offers a starting salary of $75,000-$82,000 and opportunities for professional development in a collaborative research environment. Successful applicants will work on critical climate data projects with interdisciplinary teams.