School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With more than 130 faculty members and an enrolment of more than 4,000, of which close to 1,000 are graduate students, it is one of the largest EEE schools in the world and ranks 4th in the field of Electrical & Electronic Engineering in the 2021 QS World University Rankings by Subjects.

We are looking for a Predoctoral researcher who can work as a Data Scientist, Machine Learning (ML) Researcher and ML Engineer working in collaboration with external NUS and NParks cross-functional teams. A ML model that forecasts forest growth is the goal of this project, integrating microclimate and connectivity data provided by NUS Ecology and Geospatial teams. The Researcher may also be enrolled as a part-time PhD or Master’s student at NTU, in EEE or a related programme.

Key responsibilities:

In this project, the researcher must fill the 3 roles of Data Scientist, Machine Learning (ML) Researcher and ML Engineer at a proportion of 2:5:3 respectively.

• Data Scientist: perform fieldwork and curation of remote sensing data from UAV mapping missions across multiple forested sites.

• ML Researcher: develop biodiversity classification and LIDAR canopy analysis algorithms based on UAV remote sensing data.

• ML Engineer: the system infrastructure for serving the UAV data to the research methods and provide data visualization for end-users.

• Construct a professional data portal for stakeholders to input the data and view the results using industry-standard software engineering practices.

• Liaise work between NTU, NUS and NParks to bring the project to a successful ending.

Job Requirements:

• Successful candidate should have a Master’s or Honours degree with relevant research/work experience.

• Strong academic background in remote sensing, machine learning or data science

• Proven experience in software engineering (from industry or equivalent)

• Excellent written and oral communication skills.

We regret to inform you that only shortlisted candidates will be notified.