Title: Research Associate/ Research Assistant Positions for Forest Restoration Digital Companion Project
Multiple applicants are invited to work 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 at National University of Singapore (NUS), the Department of Geography, NUS, the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), and the Asian School of the Environment, NTU. Successful candidates should be scientific-driven, able to perform field work, and manage the project tasks and outputs independently. In addition to the respective research scope described below, these positions will work collaboratively 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.
Position 1: Research Assistant / Research Associate in NUS:
Job scope: This full-time Research Assistant (with Honours degree) or Research Associate (with Master’s degree) position will ideally also be enrolled as a part-time PhD student at the NUS Department of Geography, working with A/P Wang Yi-Chen and Dr. Chua Siew Chin on the geospatial related tasks of the project. The RA is required to reconstruct land use histories and vegetation cover using GIS and remote sensing, quantify forest patch connectivity, incorporate stakeholder’s views to perform multi-criteria decision analysis, as well as contribute to modelling forest growth and ecological processes at stand to landscape scales.
Qualifications: Successful candidates should have a Master’s or Honours degree with relevant research/ work experience. The candidate is ideally able to start work between June to August 2022, with (1) academic background in geography, environmental studies, forest ecology, GIScience, or related field; (2) experience in geospatial data analysis, aerial photo interpretation, and field work; (3) strong programming skills (Python and R preferred); (4) excellent written and oral communication skills.
Interested applicants should refer to the Geography website (https://fass.nus.edu.sg/geog/application/) for PhD application requirements.
Position 2: Research Assistant / Research Associate in NTU:
Job scope: This is a full-time Research Assistant (with Honours degree) or Research Associate (with Master’s degree) position at the School of Electrical and Electronic Engineering (EEE) under Dr. Sit Ji-Jon and A/P Lee Yee Hui. The RA will ideally also be enrolled as a part-time PhD or Master’s student (by Research) at NTU, either in EEE or other related programmes. In phase 1, the RA is required to develop tree crown segmentation and tree species classification algorithms based on multi-spectral UAV photogrammetry. Lidar and 3D point cloud data may be used to augment the accuracy of the algorithms, if available. Candidates will be required to explore feature extraction and selection for classifier model training, and implement data augmentation or few-shot learning approaches to maximize a limited training dataset. In phase 2, a machine learning model to forecast forest growth from tabular data will then be built upon the outputs of the forest classifier. This model will be re-trained annually from site data across >40 forest plots, and hence a professional data portal for multiple users to conveniently enter the data and view the results must be constructed using industry-standard software engineering practices. Liaise work between NTU, NUS and NParks to bring the project to a successful ending.
Qualifications: Successful candidate should have a Master’s degree or Honours degree with relevant research/ work experience. The candidate is ideally able to start work in June/ July 2022, with (1) academic background in computer science, machine learning or data science, (2) industry experience in software engineering and (3) excellent written and oral communication skills.
Interested applicants should refer to https://www.ntu.edu.sg/eee/admissions for PhD or M.Eng. application requirements in EEE.
Position 3: Research Assistant in NUS:
Job scope: This full-time Research Assistant position at the Department of Biological Sciences NUS, will assist in various aspects of the project, 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.
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.
Application: Please submit the following by email to: Dr. CHUA Siew Chin (email@example.com), Dr. SIT Ji-Jon (firstname.lastname@example.org) and A/P WANG Yi-Chen (email@example.com) with the email subject: Forest Restoration Digital Companion Application.
- Curriculum vitae
- 2-page research statement and career goals
- Contacts of two referees (for the research associate position, one letter must be from Master/ Honours thesis advisor)
Application deadline is 1 May 2022 forPosition 1 in order to be considered for the part time PhD enrolment, and 1 June 2022 for the remaining positions. Only shortlisted applicants will be contacted for interview and where relevant, a full submission for PhD programme application.