Job Description:
Job Purpose
To make a leading contribution to the growing research in Geospatial Data Science at the College of Science and Engineering, the researcher will work with Professor Ana Basiri and the Geospatial Data Science Group at the University of Glasgow. The successful candidate will contribute to the development of cutting-edge geospatial AI tools, deliver world-leading research, develop their career and team through high-impact outputs, submit research proposals, supervise PhD and MSc students, and present at conferences and workshops.
Main Duties and Responsibilities
1. Develop innovative GeoAI solutions by combining geospatial data with APIs such as GPT, Codex, or similar to automate data processing, generate insights, and develop AI-driven geospatial applications.
2. Study and develop applications using existing Large Language Models through fine-tuning, information retrieval, and integration into software projects.
3. Apply relevant techniques including prompt engineering, data ingestion, and transformation.
4. Collaborate with the Geospatial Data Science team and external partners across industry, government, and the third sector.
5. Maintain and enhance research profile and reputation, publish in high-profile journals, and contribute to the research impact.
6. Present work at international and national conferences, seminars, colloquia, and workshops.
7. Support FAIR principles by making data and code repositories available and reproducible, and by writing blogs and technical reports.
8. Engage in personal and professional development to enhance skills.
9. Undertake any other duties as assigned by the PI.
Knowledge, Qualifications, Skills, and Experience
Essential:
* PhD or equivalent in a relevant discipline, with experience in computer science or related fields.
* Extensive knowledge of AI foundations, including prompt engineering, data ingestion, transformation, and fine-tuning models.
* Deep understanding of APIs such as OpenAI's offerings and their application to geospatial data.
* Research creativity, excellent communication and interpersonal skills, project management, self-motivation, problem-solving abilities, and capacity to design innovative solutions.
* Postdoctoral experience or equivalent, with expertise in multimodal machine learning, frameworks, and libraries, and a track record of publications.
Desirable:
* Experience with international academic collaborations, funding applications, and mentoring students.
Closing date: 1 October 2024
Terms and Conditions:
Salary: Grade 7, £39,347 - £44,263 per annum. Full-time, funding for up to 2 years. The university values diversity and inclusion, and offers flexible working options.
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