Research Associate/Fellow in Urban Analytics

1 month ago

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

To make a significant contribution to the growth of research in the Geospatial Data Science Group, this research associate/fellow will work with Professor Ana Basiri and the team to explore geospatial data using various methods and models.

This role will have the opportunity to work on newly awarded research projects, including "Missing Data as Useful Data".

The successful candidate will contribute to the formulation and delivery of world-leading research, developing their own career and team through delivering high-impact outputs, submitting research proposals, supervising PhD and MSc students, presenting and organizing conferences, seminars, and workshops in relevant areas as opportunities allow.

Main Duties and Responsibilities
  1. Quantitatively measure the implications and limitations of living in cities designed based on place-based approaches, Universal or One-Size Fits-All Approach as under-representative groups, such as elderlies or people with mobility issues.
  2. Develop a mathematical framework and communicate through visualization methods what it means to live in a city designed for "average" residents.
  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. Plan and conduct assigned research individually and/or jointly in accordance with project deliverables and project/group/School/College research strategy.
  5. 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 refereed journals, enhancing research impact in terms of economic/societal benefit, and gathering indicators of esteem.
  6. 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.
  7. Support and contribute 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. Lead and contribute to the organization, supervision, mentoring, and training of undergraduate and/or postgraduate students and less experienced members of the project team to ensure their effective development.
  10. Lead and contribute to outreach activities of the University of Glasgow, teaching or supervision activities, and associated admin as assigned by the Principal Investigator.
  11. Be responsible for safety management related to the organization 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. Undertake any other duties of equivalent standing as assigned by the PI.
Knowledge, Qualifications, Skills, and Experience

Essential:

  • 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.
  • Extensive knowledge of at least two of quantitative data analysis, (geo-) statistics, urban analytics, and simulation.
  • Extensive experience in at least one programming language (e.g., Python, R).

Desirable:

  • Good knowledge and experience of agent-based modeling, Geo-AI, or spatio-temporal data.
Skills
  • Research creativity and cross-discipline collaborative ability as appropriate.
  • Excellent communication skills (oral and written), including public presentations and ability to communicate complex data/concepts clearly and concisely.
  • Excellent interpersonal skills, including team working and a collegiate approach.
  • Self-motivation, initiative, and independent thought/working.
  • Problem-solving skills, including a flexible and pragmatic approach.
Experience

Essential:

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

For appointment at Grade 8:

  • A track record of presentation and publication of research results in quality journals/conferences.
  • Experience of making a leading contribution in academic activities.
  • 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.
  • Experience in undertaking independent research.

Desirable:

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

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