Lead, Geospatial Artificial Intelligence and Machine Learning

Yale University is seeking an experienced AI/ML professional to lead a new geospatial AI and machine learning support function through the Yale Center for Geospatial Solutions. The role will support research by advising, training, mentoring, and consulting with faculty and staff on GeoAI, generative AI, LLMs, remote sensing, computer vision, model evaluation, and secure data and model integration.

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Responsibilities

• User Training: Refine training methodologies and train and mentor users of the research core, providing guidance and expertise
• Experiment Support: Collaborate closely with researchers and lead complex projects requiring customized solutions within the research core
• Facility/Instrument Support: Lead and manage research projects within the research core
• Technique Development: Contribute to the development of research strategies within the research core and evaluate and implement cutting-edge technologies and methodologies
• Data Analysis/Interpretation: Analyze and interpret complex scientific data, providing critical insights and recommendations
• Equipment Procurement: Assist in the evaluation, acquisition, and maintenance of research core equipment
• Professional Development: Stay updated with emerging research trends and technologies. Participate and present in professional development activities and scientific conferences, representing the research core at conferences and events
• Scientific Participation: Collaborate with users on manuscript preparation and grant proposals, as applicable
• Staff Training and Mentoring: Mentor and support junior staff members in their professional growth
• Leadership: Collaborate with senior core leadership on research core-related initiatives
• Finance and Admin: Support the Core Director with development and implementation of strategic plans and budgets for the research core
• Vendor Relations: Oversees strategic vendor partnerships, manages negotiations, and evaluates vendor performance for the research core
• Education and Outreach: Develop education and outreach activities within the core, including tours, events, etc

Preferred

• 1.Demonstrated experience applying, adapting, evaluating, and tuning GeoAI, machine learning, and Earth-observation foundation models, such as Prithvi, AlphaEarth, TerraMind, or comparable models
• 2.Experience with LLM-enabled research workflows, including AI agent frameworks, and API-based model integration
• 3.Understanding and appreciation of the secure use of public and private models is essential
• 4.Experience teaching courses or workshops, developing technical training materials, or providing research consulting in an academic or interdisciplinary setting is a plus

Benefits

• Hybrid work
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• Centennial, Colorado, USA
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Qualifications

• 1. Demonstrated experience applying AI and machine learning methods to research problems, including GeoAI, generative AI, LLM-enabled workflows, computer vision, and model selection, tuning, and evaluation in interdisciplinary research settings
• 2. Fluency with modern computational environments, including Python and/or R, command-line workflows, APIs, cloud or secure computing environments, and AI/ML tools, with the ability to learn and evaluate emerging methods as the field evolves
• 3. Demonstrated understanding of research methods across the social, environmental, and data sciences, with the ability to translate faculty research questions into appropriate data, modeling, evaluation, and reproducible analytical workflows
• 4. Strong organizational skills, attention to detail, and ability to prioritize and manage multiple assignments simultaneously
• 5. Strong interpersonal skills, communication skills, and the ability to work effectively with faculty, staff, and research partners internally and externally
• Master's Degree in a related discipline and five years of related experience or an equivalent combination of skills, education, and experience
• 1.Demonstrated experience applying, adapting, evaluating, and tuning GeoAI, machine learning, and Earth-observation foundation models, such as Prithvi, AlphaEarth, TerraMind, or comparable models
• 2.Experience with LLM-enabled research workflows, including AI agent frameworks, and API-based model integration
• 3.Understanding and appreciation of the secure use of public and private models is essential
• 4.Experience teaching courses or workshops, developing technical training materials, or providing research consulting in an academic or interdisciplinary setting is a plus
• Master's Degree in a related discipline and five years of related experience or an equivalent combination of skills, education, and experience.

Required skills

• Application Programming Interfaces (APIs), Artificial Intelligence and Machine Learning, Cloud Computing, Command-Line Workflows, Computer Vision, Generative AI, GeoAI, Geospatial Foundation Models, Large Language Models (LLMs), Model Selection, Tuning, and Evaluation, Python, R, Remote Sensing, Reproducible Analytical Workflows, Secure Computing Environments

Experience

• 5+ years