GIS/RS Research fellow : Centre for Wildlife Studies (CWS)

Apply by 15th November 2024

Centre for Wildlife Studies (CWS) is a non-profit trust based in Bengaluru, India. Established in 1984, CWS is now an internationally recognized centre-of-excellence in the arenas of wildlife research, training, formal education and in situ conservation. Centre for Wildlife Studies practices science-based conservation, with special emphasis on ecology and conservation of the tiger and other large mammals. CWS works in collaboration with Central and State Governments in India to promote conservation of wildlife and wild lands, and is additionally supported by several international and national charities, agencies and donors.

Position Title: GIS/RS Research fellow
Number of Positions:  1
Location: Centre for Wildlife Studies, Bangalore
Duration: 12 months starting with the possibility of extension

Scope:

The Centre for Wildlife Studies (CWS) is seeking applications for a GIS/RS research fellow position to support a critical research project titled: Development of early warning system using AI/ML to predict forest fire occurrences in the Eastern Ghats of India.  This role will encompass extensive development of AI/ML models to predict wildfire occurrences in the Eastern Ghats and in the Kaval Tiger Reserve landscape.  Knowledge of forest fires datasets, delineation of burned areas, development of predictive models, and refinement of models are prerequisites.  Competence in the use of GIS/RS softwares, such as GEE, and related softwares will be an advantage.  Other responsibilities include data entry, data management, report writing, and other administrative tasks at our field stations or office in Bangalore.

Project Objectives:

• Prepare fire detections and burned area maps for the Eastern Ghats and the Kaval Tiger Reserve landscape.
• Identify climate, anthropogenic, and drivers of wildfires in the study areas
• Develop AI/ML models to predict fire occurrences and burned areas through model development.
• Develop an early warning system that includes variables such as climate, human, and other critical variables for fire prediction.

Key Responsibilities:

• Identify various satellite datasets and algorithms for detecting forest fires..
• Prepare the AI/ML models to predict wildfires.
• Travel to field sites and assess the performance of AI/ML models
• Develop API to host models through Power BI and train forest department staff to use the same.
• Assist in writing manuscripts, articles, and reports.
• Create outreach and communication materials as required.
• Support various project administration tasks, including but not limited to coordinating research team meetings, meticulous account keeping, grant reporting, and supervising field assistants.

Additional Opportunities:

CWS encourages professional development and will support you in pursuing opportunities to upskill. You may also engage in independent projects that align with the broader scope of the research initiative, subject to approval from your reporting manager.

Required Skills:

• A postgraduate degree in life sciences/engineering or related disciplines (e.g., environmental sciences, geography, geoinformatics), with significant experience in AI/ML.
• Significant experience in conducting GIS/RS projects.
• Experience in developing models, choice of models, identification of robust models and variables, testing and training, measures of accuracy.
• Experience with handling accounts and grant reports.
• Proficiency in spoken and written Telugu and English.
• Ability to work independently and collaboratively within a team.

Pay Scale:

Salary will be commensurate with experience.

Application Process:

To apply, please submit the following documents:

• Curriculum vitae and a cover letter expressing your interest in the position.
• A list of two professional references.
• Please send all documents to Dr. Narendran Kodandapani at narendran.kodandapani@cwsindia.org with the subject line “Application for the position of GIS Fellow.” Applications will be reviewed on a rolling basis until the positions are filled.

Note: Incomplete applications will not be reviewed.

We are committed to enhancing representation within our organization, as diverse voices and perspectives are essential for addressing the challenges of our time. Therefore, we welcome applicants of all gender identities and especially encourage female and non-binary individuals to apply (disclosure of gender identity will not be required at any point). We also encourage individuals with disabilities to apply; while fieldwork may pose certain constraints, we will strive to make accommodations to the best of our abilities. Additionally, we invite individuals from underprivileged or underserved communities, who may not have had access to the same opportunities but feel capable of fulfilling the tasks described, to apply. If you do not meet all the listed qualifications but are passionate about this opportunity, we invite you to reach out for a conversation.

We look forward to your application and the possibility of you joining our team at the Centre for Wildlife Studies.