Research Associate in Geospatial Data Science for Urban Applications

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

• The researcher will work under the supervision of the Principal Investigator (PI) to conduct academic research and administrative work.
• The candidate will be focus on research activities at the forefront of geographical information science and urban data science
• Development of software tools, methodologies, datasets, and related solutions.
• Exploring new research directions and experimenting with new datasets and technologies.
• Assisting the PI in various activities in the research group and project such as supervision/mentorship of students and junior researchers, management, and assisting with funding applications.
• Design and conduct research studies; manage collaboration with other researchers and coordination.
• Conduct literature review on appropriate topics related to the project.
• Preparation of publications and maintenance of other forms of research output such as software and data after their release.
• Attending and following meetings, conferences, and discussions with various stakeholders.

Job Requirements

You should demonstrate that you possess:

• A Master’s degree in a relevant discipline from a reputable university
• Relevant work experience of minimum 2 years
• Experience with novel forms of geospatial and urban data such as digital twins and street view imagery – in particular acquiring and processing them with state of the art techniques.
• Solid experience in programming, preferably both Python and R. A developed Github repository will be viewed favourably.
• Good experience in computer vision / deep learning and image processing.
• Excellent knowledge of the geospatial process and spatial analysis in the domain of urban studies, together with GIS tools such as QGIS and/or ArcGIS, and geospatial packages in key programming languages such as Python and R.
• Experience in scientific publications, preferably journal papers.
• Curiosity and passion to explore new concepts, methods and technologies, and capability of identifying and quickly learning the most suitable tools for the research on the go.
• The demonstrated ability to conduct research independently and a track record of interdisciplinary research will be evaluated positively.