Postdoctoral Associate (Machine Learning)

Description

The Urban Systems Lab is seeking a Postdoctoral Associate in Machine Learning to develop and optimize machine learning (ML) and AI-driven climate risk models for the ClimateIQ project. This position will refine ML approaches to provide high resolution climate hazard information and improve decision-making for city planners, policymakers and other stakeholders.

The candidate will work closely with researchers, city agencies, and industry partners to integrate advanced ML methods into climate hazard modeling and risk assessment. This role requires expertise in ML model development, geospatial analysis, and environmental data processing.

Responsibilities

• Design and optimize machine learning models (LSTM and CNN) for climate risk prediction.

• Improve data pipelines and model performance for large-scale environmental datasets.

• Develop AI-powered decision-support tools for cities and energy networks.

• Conduct research on novel AI methodologies for urban resilience.

• Publish findings in top-tier machine learning and climate science journals.

In compliance with NYC’s Pay Transparency Act, the annual base salary for this position is $72,500.  New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.

Qualifications

• PhD in Computer Science, Data Science, Environmental Engineering, or a related field.

• Experience in deep learning, predictive modeling, and AI-driven decision-support tools.

• Strong programming skills in Python, TensorFlow, or PyTorch.

• Demonstrated ability to work with large-scale geospatial and climate datasets.

Application Instructions

Please upload resume/CV

Equal Employment Opportunity Statement

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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels.

Sustainability Statement 

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