ML and Environment Postdoctoral Fellow

The University of Colorado Boulder is hiring a Postdoctoral Fellow in Machine Learning and Environmental Data Science. This role involves developing research projects, collaborating with diverse teams, and promoting open science. Candidates should have a Ph.D. in a related field, knowledge of Python and machine learning, and effective project management skills. The position offers benefits including health insurance, retirement plans, and professional development opportunities.
About the position

The University of Colorado Boulder is seeking a Post-Doctoral Research Scholar in Machine Learning (ML) and Artificial Intelligence (AI) with a focus on Environmental Data Science (EDS). This interdisciplinary fellowship aims to enhance the integration of ML/AI research with EDS, providing the fellow with a supportive network within the Computer Science Department and the Environmental Data Science Innovation and Inclusion Lab (ESIIL). The role involves developing innovative research projects, collaborating with diverse teams, and contributing to open science initiatives.

Responsibilities
• Develop and implement a research project that advances machine learning methods, analysis, and/or tools for environmental data science.
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• Work collaboratively with members of the Computer Science Department and the ESIIL network.
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• Contribute to the open, reproducible science and education objectives of ESIIL.
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• Effectively share research results with colleagues and the broader science community through publications and presentations.
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• Interact with a cohort of ESIIL postdocs and promote diversity, equity, and inclusion in open environmental data science.

Requirements
• Ph.D. in computer science, data science, or a related field.
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• Knowledge of Python programming language and machine learning packages (e.g., PyTorch).
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• Commitment to Open Science principles.
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• Effective project management skills.
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• Collaborative spirit and comfort working in diverse teams.

Nice-to-haves
• Experience with geospatial and statistical machine learning.
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• Familiarity with environmental data science applications.
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• Previous involvement in open science initiatives.

Benefits
• Medical and dental insurance coverage.
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• Retirement plans.
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• Paid time off and tuition benefits.
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• Access to regional public transit system (ECO Pass).
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• Professional development opportunities and mentorship programs.