WWF-Myanmar is now inviting applications for the "Trainer for Wildlife Monitoring Data Organizing, analysis and Modeling" to work in October and November 2026 for 2 months in Yangon, Myanmar.
Background
WWF, an independent conservation organization active in nearly 100 countries, works to sustain the natural world for the benefit of people and wildlife. WWF-Myanmar, established in 2014, is focused on halting the loss of the country's extraordinary biodiversity and ensuring that human use of the country's natural resources is sustainable and equitable. Preserving the environment in which people live and work is critical for health and wellbeing. Find out more at www.wwf.org.mm
Background of assignment/ Project
Camera trapping is one of the most widely used methods for monitoring wildlife populations, assessing species distribution, estimating abundance and density, and evaluating conservation interventions. With increasing volumes of camera trap data being collected across Myanmar, there is a growing need to strengthen the capacity of conservation practitioners, researchers, and partner organizations to effectively manage, analyze, and interpret camera trap data using robust statistical approaches.
To support evidence-based conservation decision-making, this training will provide participants with theoretical knowledge and practical skills in camera trap data management and analysis using R, with a focus on the camtrapR package and commonly used ecological modeling approaches. This training is a joint organizing with conservation organizations.
Objectives
The overall objective of the training is to build participants' capacity to process, manage, analyze, and interpret camera trap data using R and relevant ecological modeling frameworks.
By the end of the training, participants will be able to organize and manage camera trap datasets using CamptrapR, to understand principles of study design and camera trap survey planning, to conduct occupancy analyses to estimate species occurrence and habitat use, to apply N-mixture models to estimate abundance from count data, to understand and apply distance sampling concepts where appropriate, to conduct Spatially Explicit Capture-Recapture (SECR) analysis for density estimation, to conduct nest survival analysis using camera trap-derived monitoring data, to interpret model outputs and communicate findings for conservation management.
Scope of work
- Review the participants' background and training needs.
- Develop training materials, presentations, exercises, and datasets.
- Deliver a five-day training program combining lectures, demonstrations, and hands-on practical exercises.
- Guide participants through real camera trap datasets.
- Provide step-by-step instructions for data analysis in R.
- Submit all training materials and analysis scripts.
- Provide a brief training completion report including participant feedback and recommendations.
Required Profile and Expected Qualifications
- PhD, or equivalent qualification such as professor in Wildlife Ecology, Conservation Biology, Biostatistics, Quantitative Ecology, or related fields.
- Strong scientific publication record related to wildlife population assessment and conservation ecology is desirable.
- Demonstrated expertise in camera trap survey design and wildlife monitoring.
- Advanced proficiency in R programming is important.
- Proven experience using camtrapR, occupancy models, N-mixture models, SECR, and distance sampling approaches.
- Experience delivering professional training to conservation practitioners and researchers
Application Process
Interested candidates are invited to submit an application package containing 1) Technical Proposal; outlining by methodology, workplan and team composition, 2) Financial Proposal with a detailed budget breakdown covering their professional fees only and other costs (expressed as a daily rate in either USD or MMK) & 3) Supporting Documents, such as Curriculum Vitae (CV), at least one sample work and contact information for two professional references from previous similar assignments.
Submission Details
Deadline: Applications must be submitted no later than 22 September 2026 at 11:59 PM (MMT)
Submission Channel: Please send the application via email to mm.procurement@wwf.org.mm with the subject line: "Application: Trainer for Wildlife Monitoring Data Organization and Modeling."
WWF's Policies and Acknowledgement
The Consultant shall at all times ensure and comply with any applicable laws and regulations and WWF's policies. The Consultant must sign for: (1) Fraud and Corruption Prevention (2) Investigation Policy (3) WWF Network Commitment to Integrity and (4) WWF Network Terms & Conditions before undertaking the service to a high standard using the best endeavour's.