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A leading research university is seeking a research assistant in the geospatial and data science domain. The role includes conducting research activities, project management, and software development. Candidates must possess a Master's degree in a related field, expertise in statistics, and programming skills, particularly in Python. Excellent communication skills are essential for collaboration and presentation of research outcomes.
Interested applicants are invited to apply directly at the NUS Career Portal
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We regret that only shortlisted candidates will be notified.
We are seeking a research assistant to assist with a project and research in the geospatial & data science domain.
The primary tasks are:
• Conducting research activities.
• Literature reviews.
• Project management and administration.
• Development of software tools and related solutions.
• Collaboration with other researchers and coordination, and co-authoring publications and other forms of output.
• 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, management, administration, and funding applications.
• Preparation of publications and managing other forms of research output such as software and data.
• A Master’s degree in a related discipline (e.g. urban planning, geographic information science, computer science). Current master students are eligible to apply as well, provided that they are in the final stage of their studies and that their degree will be completed before the start of the appointment.
• An ability to conduct research independently.
• Expertise in statistics.
• Expertise in geospatial technologies.
• Experience in research, preferably with publications and other forms of relevant outputs.
• Excellent communication skills in English, writing skills, and an ability to present research in both academic and non-academic venues.
• Experience with programming (primarily Python) and machine learning libraries.
• 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.
• A positive and proactive stance on open science, preferably with demonstrated activities such as using and developing open-source software, releasing data as open data, and promoting reproducible research.