Geospatial AI Research Scientist

2 months ago

Glasgow, Glasgow City, United Kingdom University of Glasgow Full time
Job Purpose

To make a significant contribution to the advancement of Geospatial Data Science at the University of Glasgow, the researcher will collaborate with Professor Ana Basiri and the Geospatial Data Science Group. The successful candidate will make a substantial contribution to the development of cutting-edge geospatial AI tools, delivery of world-leading research, and career development through delivering high-impact outputs, submission of research proposals, supervision of PhD and MSc students, and presentation at conferences, seminars, and workshops.

Main Duties and Responsibilities
  • Develop innovative GeoAI solutions by combining geospatial data with OpenAI's and/or similar API offerings to leverage these tools for geospatial data tasks and use these APIs to automate data processing, generate insights, and develop AI-driven geospatial applications.
  • Study and develop applications using existing Large Language Models through fine-tuning, information retrieval, and integration into wider software projects.
  • Study and use relevant techniques including prompt engineering, data ingest and transformation techniques.
  • Collaborate with the growing team in Geospatial Data Science at the University of Glasgow and collaborators across industry, Government, and third sector.
  • Maintain and enhance your research profile and reputation and that of the University of Glasgow and research team, including contributing to publications of international quality in high-profile refereed journals, enhancing the research impact in terms of economic/societal benefit, and gathering indicators of esteem.
  • Presentation of work at international and national conferences, at internal and external seminars, colloquia, and workshops to develop and enhance our research profile.
  • Supporting and contributing to FAIR principles, i.e., findability, accessibility, interoperability, and reusability of research in geospatial data science within the school and the college by, for example, making data and code repositories available and reproducible, writing blogs, drafting technical/progress reports, and papers as appropriate.
  • Engage in personal, professional, and career development to enhance both specialist and transferable skills in accordance with desired career trajectory.
  • Undertake any other duties of equivalent standing as assigned by the PI.
Knowledge, Qualifications, Skills, and ExperienceKnowledge/Qualifications Essential:
  • A1 An awarded PhD, Scottish Credit and Qualification Framework level 12, or equivalent professional qualifications in a relevant academic/research discipline, and experience of personal development in one of the areas of computer science or similar disciplines.
  • A2 Extensive knowledge of foundations of AI including prompt engineering, data ingest and transformation techniques, and fine-tuning models.
  • A3 Deep understanding of OpenAI's and/or similar API offerings, and how to leverage these tools for geospatial data tasks. Proficiency in using these APIs to automate data processing, generate insights, and develop AI-driven geospatial applications.
Skills Essential:
  • C1 Research creativity and cross-discipline collaborative ability as appropriate.
  • C2 Excellent communication skills (oral and written), including public presentations and ability to communicate complex data/concepts clearly and concisely.
  • C3 Excellent interpersonal skills including team working and a collegiate approach.
  • C4 Appropriate workload, time, project, budget, and people management skills.
  • C5 Self-motivation, initiative, and independent thought/working.
  • C6 Problem-solving skills including a flexible and pragmatic approach.
  • C7 Capability to design and implement innovative solutions to address geospatial challenges through AI and multimodal learning approaches.
Experience Essential:
  • E1 Sufficient relevant postdoctoral experience or equivalent.
  • E2 A Deep understanding of multimodal machine learning techniques, including the integration and fusion of data from various sources (e.g., images, text, sensor data).
  • E3 Experience with machine learning frameworks and libraries.
  • E4 Proven ability to deliver quality outputs in a timely and efficient manner.
  • E5 Evidence of an emerging track record of publications in a relevant field.
  • E6 Ability to conduct research and stay updated with the latest advancements in geospatial AI and multimodal learning.
Desirable:
  • F1 Experience with collaborating with or working at international academic environments of the highest national or international quality.
  • F2 Experiences with identifying and developing funding applications as appropriate.
  • F3 Support of less experienced members of the project team e.g., postgraduate and project students.

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