Research Software Engineer: Geospatial Artificial Intelligence (Geo-AI)

University of Glasgow
Glasgow
1 year ago
Create job alert

Job Purpose

 To make a leading contribution to the growing research in Geospatial Data Science at the College of Science and Engineering, this research associate/fellow will work with Professor Ana Basiri and the Geospatial Data Science Group, at the University of Glasgow. The successful candidate will make (a leading) contribution to the development of cutting-edge geospatial AI tools, delivery of world-leading research, develop their career and team through delivering high-impact outputs, submission of research proposals to develop their team and research, supervision of PhD and MSc students, presenting at conferences, seminars and workshops in the relevant areas as opportunities allow. Main Duties and Responsibilities Perform the following activities in conjunction with the team: 1. Investigate and develop generative geospatial AI and Large Language Models for geospatial data (GeoAI).2, Develop innovative GeoAI solutions by combining geospatial data with OpenAI's and/or similar API offerings, such as GPT, Codex, etc to leverage these tools for geospatial data tasks and use these APIs to automate data processing, generate insights, and develop AI-driven geospatial applications.3. Study and develop applications using existing Large Language Models through fine-tuning, information retrieval, and integration into wider software projects.4. Study and use relevant techniques including prompt engineering, data ingest and transformation techniques.5. Collaborate with the growing team in Geospatial Data Science Team at the University of Glasgow and the collaborators across industry, Government, and third sector.6. Develop 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/quality refereed journals, enhancing the research impact in terms of economic/societal benefit, and gathering indicators of esteem.7. Lead and contribute to the presentation of work at international and national conferences, at internal and external seminars, colloquia and workshops to develop and enhance our research profile.8. 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.9. Engage in personal, professional and career development to enhance both specialist and transferable skills in accordance with desired career trajectory.10. Undertake any other duties of equivalent standing as assigned by the PI. Knowledge/Qualifications Essential: A1 An awarded PhD, Scottish Credit and Qualification Framework level 12, or equivalent professional qualifications in 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 conciselyC3 Excellent interpersonal skills including team working and a collegiate approachC4 Appropriate workload, time, project, budget, and people management skillsC5 Self-motivation, initiative and independent thought/workingC6 Problem solving skills including a flexible and pragmatic approach Experience Essential: E1 Sufficient depth of relevant research experience, normally including sufficient postdoctoral experience in a related field, appropriate to an early career researcher.E2 Experience in projects that involve the application of OpenAI and/or similar APIs to solve real-world (geospatial) problems and to implement and deploy GeoAI solutions effectively.E3 Demonstrated experience integrating such APIs with geospatial software and platforms (e.g., ArcGIS, QGIS, Google Earth Engine) to enhance spatial data analysis, and decision-making processes.E4 Proven ability to deliver quality outputs in a timely and efficient mannerE4 Evidence of an emerging track record of publications in a relevant field Desirable: F1 Experience with collaborating with or working at international academic environments of the highest national or international qualityF2 Experiences with identifying and developing funding application as appropriateF3 Support of less experienced members of the project team e.g. postgraduate and project students Closing date: 1 October 2024 Terms and Conditions Salary will be Grade 7, £39,347 - £44,263 per annum. This post is full time, and has funding for up to 2 years As part of Team UofG you will be a member of a world changing, inclusive community, which values ambition, excellence, integrity and curiosity. The University of Glasgow has a responsibility to ensure that all employees are eligible to live and work in the UK. If you require a Skilled Worker visa to work in the UK, you will be required to meet the eligibility requirements of the visa route to be assigned a Certificate of Sponsorship. As a valued member of our team, you can expect:1 A warm welcoming and engaging organisational culture, where your talents are developed and nurtured, and success is celebrated and shared. 3 A flexible approach to working.

Related Jobs

View all jobs

Senior Data Scientist

Machine Learning Research Engineer - NLP / LLM

Machine Learning Research Engineer – NLP / LLM

Machine Learning Research Engineer – NLP / LLM

Machine Learning Research Engineer - NLP / LLM - RedTech Recruitment

Machine Learning Research Engineer - NLP / LLM

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.