{"id":13025,"date":"2025-11-24T05:53:37","date_gmt":"2025-11-24T10:53:37","guid":{"rendered":"https:\/\/web.uri.edu\/maf\/?p=13025"},"modified":"2025-11-24T05:53:58","modified_gmt":"2025-11-24T10:53:58","slug":"marine-affairs-coastal-resilience-lab-recruiting-for-a-phd-student","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/maf\/2025\/11\/24\/marine-affairs-coastal-resilience-lab-recruiting-for-a-phd-student\/","title":{"rendered":"Marine Affairs Coastal Resilience Lab recruiting for a PhD student"},"content":{"rendered":"\n<p><strong><u>PhD Position in Coastal Resilience and AI-Driven Risk Management<\/u><\/strong><\/p>\n\n\n\n<p>The <strong>Department of Marine Affairs (MAF)<\/strong> at the <strong>University of Rhode Island (URI)<\/strong> invites applications for a <strong>fully funded PhD position<\/strong> in <em>Coastal Resilience and AI-Driven Risk Management<\/em>, with a focus on <strong>leveraging Artificial Intelligence (AI)<\/strong> to improve natural hazard early warning systems and decision-support tools for coastal communities.<\/p>\n\n\n\n<p>This student will work with the <strong>Coastal Hazards Analysis Modeling and Prediction system (CHAMP)<\/strong> (https:\/\/www.richamp.org), a cutting-edge initiative that integrates advanced modeling, stakeholder engagement, and decision-support to help communities prepare for and adapt to coastal hazards such as storm surge, flooding, and sea-level rise. CHAMP combines <strong>physical science models<\/strong> with <strong>social science insights<\/strong> to create actionable tools for planners, emergency managers, and policymakers.<\/p>\n\n\n\n<p>The successful candidate will join the <strong>Marine Affairs Coastal Resilience Lab (MACRL)<\/strong>, working in an interdisciplinary environment alongside ocean engineers, oceanographers, civil engineers, and social scientists under the supervision of <strong>Dr. Austin Becker<\/strong>.<\/p>\n\n\n\n<p><strong>Research Focus <\/strong>This PhD project will explore <strong>innovative applications of AI<\/strong>, such as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>AI for Risk Communication and Decision Support<\/strong>\n<ul class=\"wp-block-list\">\n<li>How can AI-driven tools (e.g., chatbots, adaptive dashboards) or infomatics improve communication of complex hazard forecasts to diverse endusers?<\/li>\n\n\n\n<li>Explore how natural language processing (NLP) can tailor messages for clarity, cultural relevance, and trust-building before and during emergency preparedness and response.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Decision Support for Emergency Management and Planning<\/strong>\n<ul class=\"wp-block-list\">\n<li>Develop AI-assisted frameworks that help local planners and emergency managers prioritize resilience investments based on social vulnerability, infrastructure risk, and community feedback.<\/li>\n\n\n\n<li>Investigate how machine learning can synthesize stakeholder input and scenario data to support transparent, equitable decision-making.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Social Dimensions of AI Integration in Coastal Resilience<\/strong>\n<ul class=\"wp-block-list\">\n<li>Examine public perceptions, ethical considerations, and governance challenges of using AI in hazard planning.<\/li>\n\n\n\n<li>Research how trust in AI systems influences adoption by municipalities and emergency agencies, and design strategies to increase transparency and accountability.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p><strong>Ideal Candidate Profile<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Masters degree in <strong>social sciences<\/strong>, <strong>geographic information systems (GIS)<\/strong>, or other interdisciplinary fields related to coastal resilience.<\/li>\n\n\n\n<li>Familiarity with <strong>AI concepts<\/strong>, <strong>GIS<\/strong>, and\/or <strong>computer programming (e.g., Python)<\/strong> is strongly preferred.<\/li>\n\n\n\n<li>Strong interest in applying AI to real-world challenges in hazard modeling, risk communication, and decision-making.<\/li>\n\n\n\n<li>US Citizen, but qualified international candidates eligible for student visas are also welcome to apply<\/li>\n<\/ul>\n\n\n\n<p><strong>Why URI and Marine Affairs?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>National leadership in ocean and coastal research<\/strong>, home to the Graduate School of Oceanography and strong interdisciplinary programs.<\/li>\n\n\n\n<li><strong>One of the few programs worldwide<\/strong> focused on the intersection of social science, policy, and coastal management.<\/li>\n\n\n\n<li><strong>Access to state-of-the-art facilities<\/strong>, coastal field sites, and a vibrant research community on the Kingston campus.<\/li>\n\n\n\n<li><strong>Environmental Data Center (EDC)<\/strong> provides expertise in geospatial analysis, data visualization, and decision-support tools\u2014critical for integrating AI and GIS into coastal resilience research.<\/li>\n<\/ul>\n\n\n\n<p>This position is fully funded, and the PhD student will receive full tuition coverage along with academic-year stipend, as listed on URI\u2019s website. The ideal start semester is Spring 2026, although a summer or Fall start is also fine.<\/p>\n\n\n\n<p>Interested candidates should contact <strong>Dr. Austin Becker<\/strong> (abecker@uri.edu) with the subject line: <em>\u201cPhD Application in Coastal Resilience and AI-Driven Risk Management.\u201d<\/em> Please include: 1) your experience or background related to these topics, 2) a brief description of how your AI skills could be applied to hazard assessment or risk communication given access to data and a system like CHAMP, 3) a PDF version of your CV, 4) Unofficial transcripts. After initial review, we will invite selected candidates to submit a full application through the URI graduate application system at <a href=\"https:\/\/web.uri.edu\/graduate-school\/apply\/\">https:\/\/web.uri.edu\/graduate-school\/apply\/<\/a>. More information on the MAF PhD program and how to apply can be found at <a href=\"https:\/\/web.uri.edu\/maf\/academics\/ph-d\/\">https:\/\/web.uri.edu\/maf\/academics\/ph-d\/<\/a>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<p><strong>The University of Rhode Island<\/strong> is a comprehensive doctoral research university and a Land, Sea, and Urban Grant institution, recognized as an R1 university for its high level of research activity. Located in a beautiful coastal town, URI offers abundant access to nature and ocean while being conveniently located near Boston and New York City, providing students with both a serene environment and proximity to major urban areas. The Department of Marine Affairs, the first of its kind in the United States and internationally recognized, offers a multidisciplinary program with a social science focus (<a href=\"https:\/\/web.uri.edu\/maf\/\">https:\/\/web.uri.edu\/maf\/<\/a>).<\/p>\n","protected":false},"excerpt":{"rendered":"<p>PhD Position in Coastal Resilience and AI-Driven Risk Management The Department of Marine Affairs (MAF) at the University of Rhode Island (URI) invites applications for a fully funded PhD position in Coastal Resilience and AI-Driven Risk Management, with a focus on leveraging Artificial Intelligence (AI) to improve natural hazard early warning systems and decision-support tools [&hellip;]<\/p>\n","protected":false},"author":809,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[],"class_list":["post-13025","post","type-post","status-publish","format-standard","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/posts\/13025","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/users\/809"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/comments?post=13025"}],"version-history":[{"count":1,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/posts\/13025\/revisions"}],"predecessor-version":[{"id":13026,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/posts\/13025\/revisions\/13026"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/media?parent=13025"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/categories?post=13025"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/maf\/wp-json\/wp\/v2\/tags?post=13025"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}