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Research Associate

1 month ago

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

Job Purpose

To make a leading contribution to the growing research in the Geospatial Data Science Group, this research associate/fellow will work with Professor Ana Basiri and the team to learn from geospatial data using various methods and models. This post will have the opportunity to work on newly awarded research projects, including "Missing Data as Useful Data," where new forms of data are considered useful to be integrated/triangulated with traditional data to provide a reliable, timely, and updated understanding of fast-changing real-world phenomena. This will be examined by nationally important and strategic applications, including managing under-reported crime, better social care, and protection of society, inclusive city planning, and dynamic census using administrative and alternative data.

Main Duties and Responsibilities

  1. Investigate the balance of high-quality survey data and large sample-sized "new forms of data" to deal with bias and under-representation issues of AI from a geographic perspective, ultimately developing an inclusive and explainable geo-AI.
  2. Develop a statistical framework to consider "new forms of data" as useful data to be integrated/triangulated with traditional data.
  3. Collaborate with the Geospatial Data Science team 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.
  4. Take a leading role in the planning and conduct of assigned research individually and/or jointly in accordance with project deliverables and project/group/School/College research strategy.
  5. Enhance and maintain 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 research impact in terms of economic/societal benefit, and gathering indicators of esteem.
  6. Presentation of work at international and national conferences, at internal and external seminars, colloquia, and workshops to develop and enhance research profile.
  7. 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 making data and code repositories available and reproducible, writing blogs, drafting technical/progress reports, and papers as appropriate.
  8. Collaborate with colleagues and participate in team/group meetings/seminars/workshops across the research team and the University and wider community.
  9. Take the lead on 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.
  10. Contribute to outreach activities of the University of Glasgow and carry out modest teaching or supervision activities and associated admin as assigned by the Principal Investigator.
  11. Be responsible for safety management related to the organisation and running of Laboratory and/or Experimental techniques, equipment, and processes as appropriate.
  12. Engage in personal, professional, and career development to enhance both specialist and transferable skills in accordance with desired career trajectory.
  13. 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.
  14. Undertake any other duties of equivalent standing as assigned by the PI.

Knowledge, Qualifications, Skills, and Experience

Essential:

  1. A PhD in a relevant academic/research discipline, and experience of personal development in one of the areas of statistics, mathematics, computer science, quantitative geography, or similar disciplines.
  2. Extensive knowledge of quantitative data analysis, (geo-) statistics, imputation, inference systems, and simulation.
  3. Extensive experience in at least one programming language (e.g., Python, R).

Desirable:

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

Skills:

  1. Research creativity and cross-discipline collaborative ability as appropriate.
  2. Excellent communication skills (oral and written), including public presentations and ability to communicate complex data/concepts clearly and concisely.
  3. Excellent interpersonal skills, including team working and a collegiate approach.
  4. Self-motivation, initiative, and independent thought/working.
  5. Problem-solving skills, including a flexible and pragmatic approach.

For appointment at Grade 8:

  1. Good Team Leadership skills.

Experience:

  1. Sufficient postdoctoral experience or equivalent in a related field.
  2. Experience of scientific writing.
  3. Proven ability to deliver quality outputs in a timely and efficient manner.

For appointment at Grade 8:

  1. A track record of presentation and publication of research results in quality journals/conferences.
  2. Experience of making a leading contribution in academic activities.
  3. Ability to demonstrate a degree of independence as illustrated by identification of project objectives from assessment of the literature, design & analysis of experiments & drafting of papers.
  4. Experience in undertaking independent research.

Desirable:

  1. Experience with collaborating with or working at international academic environments of the highest national or international quality.
  2. Experiences with identifying and developing funding applications as appropriate.
  3. Support of less experienced members of the project team, e.g., postgraduate and project students.

For appointment at Grade 8:

  1. An emerging national or international reputation.