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Job: Student Research Assistant (Digitization)

Job Title: Student Research Assistant (Digitization)

Project Title: Linking the Digital Humanities to Biodiversity History in Singapore and Southeast Asia

Project Description: This project looks at the proliferation and establishment of invasive species in Singapore and wider Southeast Asia, tracking their distribution overtime. The end product of this project is an interactive map that shows changes in biodiversity of invasive species overtime to draw connections with historical and current environmental changes and events.

Job Description:
• Key activities include:
o Digitization of library materials for data mining and cataloguing purposes
o Be onsite to carry out cataloguing of books
o Learn the cataloguing module in Sierra, the library system
o Learn basic cataloguing tools like MARC tags, RDA, etc.
o Check for duplicate titles against the library system
o If no duplicates are found, check for matching records and overlay where necessary
o Update the bibliographic record
o Add/update the item records

• Qualifications
o Proactive and good communicator
o Able to work independently as well as collaborate with others
o Detail-oriented
o Experience with digitization, data mining, data entry, and OCR is a plus
o Proficiency in Southeast Asian languages a plus

• Expected workload: 20 hours/month

Duration
May 2022 – May 2023

Renumeration
$20/hour

To apply
Informal enquiries may be made to Ms. Tricia Cho (triciacho@nus.edu.sg). Please include a cover letter and full CV your application. Only shortlisted applicants will be notified.

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Job (Apr 2022): Intertidal Fauna Specialist (1-year contract) @ Camphora

Job: Intertidal Fauna Specialist (Contract) at Camphora

Camphora is a collective that provides integrated flora, fauna and arboriculture baseline data to inform design intent and formulate solutions for ecological conservation.

We are seeking to hire an enthusiastic and self-motivated individual who has a passion for biodiversity and enjoys working in the outdoors.

You will mainly be assisting in the following (but not limited to):

  • Planning and execution of marine and terrestrial surveys
  • Integrate biodiversity findings into biodiversity impact assessment
  • Conduct inspections at development sites
  • Manage project deliverables
  • Report writing 
  • Attend and prepare for meetings  

Job Requirements

  • Diploma/Degree in Environmental Science or related fields; with background in marine ecology
  • Passionate about biodiversity conservation
  • Responsible, independent, and possess strong interpersonal skills 
  • Physically fit, and comfortable being outdoors and in the forest
  • Able to work in a fast-paced environment and meet project deadlines
  • Familiarity with identification of marine/intertidal fauna to species level, and further specific ID skills in molluscs and/or crustaceans will be an advantage
  • Knowledge in GIS or data analytic will also be an advantage

Applicants with at least 2 years of work experience preferred, but fresh graduates are welcomed to apply. 

The appointment will be on a 1-year contract basis and salary will commensurate with
qualification and experience.

To apply, please send a cover letter and CV to Derek Yap at derek@camphora.com.sg.

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Jobs (Apr 2022): Two RA positions (data centric) with the “Linking the Digital Humanities to Biodiversity History in Singapore and Southeast Asia” project

Yale-NUS is advertising two research positions for 2nd upper honours or MSc graduates (science preferred but not necessary):

  1. Research Assistant (Data Selection – Plants) [see requirements here: Yale-NUS RA_data selection plants_JD.pdf]
  2. Research Assistant (Database Coordinator) [see requirements here: Yale-NUS RA_database coordinator_JD.pdf]

These interesting positions are offered under the project, “Linking the Digital Humanities to Biodiversity History in Singapore and Southeast Asia”.

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Job (Apr 2022): Wildlife Forensics @ NParks (9-month contract)

NParks has advertised this position

You will be part of the Centre for Animal and Veterinary Service (CAVS) team under the Professional and Scientific Services (PSS) Division and the Centre for Wildlife Forensic’s (CWF) Molecular diagnostics team.

As a member of the multi-disciplinary team at the CAVS and CWF, you will be responsible for providing professional and competent diagnostic and test development support. Training will be provided in molecular techniques such as whole-genome sequencing and Single Nucleotide Polymorphism) discovery.

Duties include:

  • Developing, establishing, and validating various molecular techniques for the identification of wildlife samples.
  • Developing, establishing, and validating genotyping techniques for the determination of the genetic geographic provenance and population assignment of wild animals.
  • Participate in the maintenance of a laboratory quality system according to ISO17025:2017.

Please read details at the Careers @ Gov portal.

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Job (Apr 2022): Full-time Teaching Assistant (FTTA) for the MSc in Biodiversity Conservation and Nature-based Climate Solutions @ NUS DBS

Job: Graduate in life sciences or related degree: Full-time Teaching Assistant (FTTA) for the MSc in Biodiversity Conservation and Nature-based Climate Solutions at Department of Biological Sciences 

The FTTA will support the fieldwork, computer labs (R, data analysis and spatial modelling) and manage guest lectures and internship opportunities for the programme.

Please see Careers @ NUS: https://careers.nus.edu.sg/NUS/job/Kent-Ridge-Teaching-Assistant-%28Biological-Sciences%29-Kent/8190544/

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Jobs: RA (BSc Hons, Diploma or MSc) with PhD opportunity on a forest restoration project

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 (siewchin@nus.edu.sg), Dr. SIT Ji-Jon (jijon@ntu.edu.sg) and A/P WANG Yi-Chen (yi-chen.wang@nus.edu.sg) 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.