We are particularly interested in candidates who bridge environmental or climate science with human–environment perspectives and employ advanced geospatial, computational, or data-intensive approaches, such as spatial and spatiotemporal modeling, machine learning and artificial intelligence, sensor or mobility data, and high-performance computing, as well as qualitative, participatory, or integrated methods that complement these approaches. • Research expertise in environmental or climate science with human-environment perspectives using advanced geospatial, computational, or data-intensive approaches, such as spatial and spatiotemporal modeling, machine learning and artificial intelligence, sensor or mobility data, and high-performance computing, as well as qualitative, participatory, or integrated methods that complement these approaches.