Research Associate/fellow in Geospatial Data

3 weeks ago

Glasgow, United Kingdom University of Glasgow Full time

**Job Purpose**
To make a leading contribution to the growing research in Geospatial Data Science within the College of Science and Engineering, this research associate/fellow will work with Professor Ana Basiri and the growing team to learn from geospatial data using variety of methods and models.
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**Main Duties and Responsibilities**
Perform the following activities in conjunction with the other researchers and under the guidance of Prof Basiri:

1. Study bias and under-representation issues of AI from a geographic perspective, to ultimately develop an inclusive and explainable geo-AI.
2. Collaborate with the growing team in Geospatial Data Science at the University of Glasgow, and project partners
- including Ordnance Survey GB, Google, Microsoft Research, Uber, Meta, and the Alan Turing Institute - to support the co-design and development of inclusive and responsible technologies.
3. Plan and conduct assigned research individually and/or jointly in accordance with the project deliverables and project/group/School/College research strategy.
4. 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.
5. 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.
6. 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.
7. Take a leading role in the identification of potential funding sources and to assist in the development of proposals to secure funding from internal and external bodies to support future research.
8. Take a leading role in developing and maintaining collaborations with colleagues across the research group/School/College/University and wider community (e.g. Academic and Industrial Partners).
9. Take a leading role in team/group meetings/seminars/workshops and School research group activities to enhance the wider knowledge, outputs and culture of the School/College.
10. Take the lead in the organisation, supervision, mentoring and training of undergraduate and/or postgraduate students and less experienced members of the project team to ensure their effective development.
11. Engage in personal, professional and career development to enhance both specialist and transferable skills in accordance with desired career trajectory.
12. Undertake any other duties of equivalent standing as assigned by the PI.
13. Contribute to the enhancement of the University’s international profile in line with the University’s Strategic Plan, World Changers Together.

**For appointment at grade 8**-These key tasks are not intended to be exhaustive but simply highlight a number of major tasks which the staff member may be reasonably expected to perform.

**Knowledge, Qualifications, Skills and Experience**

**Knowledge/Qualifications**

**Essential**:

A1 An awarded (or recently submitted or near completion) 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 statistics, mathematics, computer science, quantitative geography, or similar disciplines.
A2 Extensive (theoretical and practical) knowledge of quantitative data analysis, (geo-) statistics, imputation, inference systems, and simulation
A3 Extensive experience at least in one programming language (e.g. Python, R)

**Desirable**:

B1 Good knowledge and experience of machine learning, geospatial data, or spatio-temporal data

**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 Self-motivation, initiative and independent thought/working
C5 Problem solving skills including a flexible and pragmatic approach

**For appointment at grade 8**:

C6 Good Team Leadership skills

**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 of making a leading contribution in academic activities.
E3 Experience in undertaking independent research
E4 A track record of presentation and publication of

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