Job Description
This full-time Research Assistant position at the Department of Biological Sciences NUS will be working on a 5-year interdisciplinary project entitled “Forest Restoration Digital Companion: A Social-Ecological-Technical Systems Approach”. The project, which collaborates across the fields of forest ecology, remote sensing, machine learning and spatial data science, will develop a suite of models and digital tools consolidated into a single platform to assist forest restoration work end-to-end in forecasting restoration outcomes, site prioritization, recommending actions and logistics, and monitoring for adaptive feedback. The project aims to improve our understanding of forest regeneration in Singapore and the efficacy of restoration approaches in achieving carbon sequestration and biodiversity conservation targets. The project is a collaboration among the Department of Biological Sciences (NUS), the Department of Geography (NUS), the School of Electrical and Electronic Engineering (NTU), and the Asian School of the Environment (NTU).
The Research Assistant will assist in various aspects of including administrative tasks, field work coordination, plot data collection, implementing restoration experiments, ecological measurements, laboratory analyses and data management. Successful candidate should also have excellent organization and interpersonal skills to coordinate community partners, as well as proficiency in quantitative research and analysis skills. The Research Assistant could be involved in data analysis and forest modelling at species to stand level using demographic and plant traits data. The position will also work collaboratively with others to integrate results from the project tasks to develop a digital tool GUI web-hosted on GPU server, with a companion app for forecasting and reporting forest recovery status. Successful candidate should be scientific-driven, able to perform field work, and manage the project tasks and outputs independently.
Application: Please submit the following by email to: Dr. CHUA Siew Chin ([email protected] ), A/P WANG Yi-Chen ([email protected] ) and Dr. SIT Ji-Jon ([email protected] >) with the email subject: Forest Restoration Digital Companion Application.
- Curriculum vitae
- 2-page research statement and career goals
- Contacts of three referees
Application deadline is 1 June 2022. Only shortlisted applicants will be contacted for interview.
Qualifications
Successful candidates should have a Honours degree or Diploma with relevant work experience. Candidates should have (1) academic background in forest ecology, environmental studies, botany or related fields; (2) good written and oral communication skills. The candidate is ideally able to start work in June 2022.
Covid-19 Message
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.
In accordance with Singapore's legal requirements, unvaccinated workers will not be able to work on the NUS premises with effect from 15 January 2022. As such, job applicants will need to be fully COVID-19 vaccinated to secure successful employment with NUS.
More Information
Location: Kent Ridge Campus
Organization: National University of Singapore
Department : Department of Biological Sciences
Employee Referral Eligible: No
Job requisition ID : 14514
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