阿伯丁大学位于苏格兰北部城市阿伯丁,是英国著名的教育和研究中心,世界研究型大学。该大学的教学和研究质量举世闻名,拥有 5 名诺贝尔奖得主,产生过多项重大发明。
阿伯丁大学包含多个学院,提供博士学位项目。一个项目要求使用人工智能和遥感技术研究环境变化,工作重点是开发深度学习方法。该博士项目为期 4 年,全额资助,2023 年 10 月开始。
项目要求计算机或相关专业背景,有机器学习经验优先。申请需提交个人简历、成绩证明、推荐信等材料。
博士项目简介 AI, Deep Learning, and Remote Sensing to study Environmental Change （人工智能、深度学习和遥感研究环境变化--计算机科学哲学博士学位） 相关领域： Data and AI, Energy Transition, Environment and Biodiversity, Health Wellbeing and Nutrition, and Social Inclusion and Cultural Diversity 项目简介 This is a 4-year, fully funded project. Funding is provided by the University of Aberdeen Interdisciplinary Research initiative, which will recruit 20 Interdisciplinary Fellows and 12 Interdisciplinary PhD students in total over the next year, across five challenge areas, namely Data and AI, Energy Transition, Environment and Biodiversity, Health Wellbeing and Nutrition, and Social Inclusion and Cultural Diversity. The student will be part of this cohort and will benefit from other activities and interactions. The expected start date for this project is October 2023 or earlier (negotiable) 工作任务 This 4-year interdisciplinary PhD studentship will be based in the Interdisciplinary Centre for Data and AI, and benefit from resources from within the Schools of Natural and Computing Sciences and Geosciences (e.g. facilities/HPC). The aim is to conceptualise new deep learning approaches, with a particular focus on self-supervised transformer and diffusion models for representation learning that will exploit large-scale multimodal datasets from remote sensing and other sources, such as satellites, drones and sensor networks. From a technical standpoint, it is intended that this PhD will build upon approaches described in, to contribute to foundational research in deep learning. It is anticipated that some early-stage developments will require the use of large-scale benchmark vision datasets, e.g. Imagenet. The first 6 months of the project will be primarily spent exploring avenues and open problems within self-supervised learning, multimodal deep learning, and remote sensing, and establishing a deep understanding of how it can be used to improve our understanding of environmental change in locations such as the Arctic. A PhD proposal will be due on month 9. 申请条件 Honours degree (minimum 2:1) in Computer Science, Engineering, Mathematics, or another technical discipline which included a major focus on programming and problem solving, and ideally on machine learning and AI. It is essential that the student has demonstrable experience (e.g. transcript record) programming in python (a personal github repository with a portfolio would be advantageous). Good knowledge of other programming languages, linear algebra, and probabilities is also required. some knowledge of climate science, environmental sciences, or geosciences a master’s degree in AI, Machine Learning, Environmental Sciences, Climate Science, Geosciences or similar, is highly desirable and will be given significant weight during the shortlisting process Dissertation/Thesis in the area of deep learning, e.g. self-supervised learning, will be advantageous 申请程序 Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php You should apply for Degree of Doctor of Philosophy in Computing Science to ensure your application is passed to the correct team. Please clearly note the name of the supervisor and project title on the application form. If you do not mention the project title and the supervisor on your application it will not be considered for the studentship. Please include a cover letter specific to the project you are applying for (max 1 page, addressed to Dr Georgios Leontidis), an up-to-date copy of your academic CV, undergraduate and postgraduate educational certificates and full transcripts. Please note: you DO NOT need to provide a research proposal with this application
