INTERNAL CALL ONLY (RFP300765) - Research Associate (Climate Modeler) - Digital Inclusion

Overview

Support climate modelling efforts for agricultural analysis.

You have:

• A Bachelor degree in a relevant field (e.g., Agricultural meteorology, climate science, ecology, environmental science) with minimum 2 years of work experience.
• Proficiency in quantitative and qualitative research methods.
• Strong programming skills for model development (e.g., Python, R).
• Strong working knowledge of GIS.
• Familiarity with climate modeling tools, remote sensing techniques, and relevant software.
• Excellent communication skills and the ability to collaborate across disciplines.
• Ability to work collaboratively in a team environment.
• Ability to communicate complex ideas effectively, verbally and in writing, in English.

Job Description

The Organization

The International Center for Tropical Agriculture (CIAT) is part of the Alliance of Bioversity International and CIAT. CIAT delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people’s lives. CIAT solutions address the global crisis of malnutrition, climate change, biodiversity loss, and environmental degradation.

CIAT works with local, national and multinational partners across Latin America and the Caribbean, Asia and Africa, and with the public and private sectors. CIAT is part of CGIAR, a global research partnership for a food-secure future, dedicated to transforming food, land and water systems in a climate crisis.

About the position

CIAT is looking for a skilled climate modeler to support the agroclimatology team in crop-climate modelling. This work will feed into a user-friendly platform which enables private sector sourcing companies, agronomic teams, farmers, and researchers to explore climate layers, risk and opportunity areas for crop production as well as environmental trends over time.

Key duties and responsibilities

Research and Analysis:

• Support crop analysis efforts by assisting in data collection and in-depth analysis on crop physiology, productivity and trend analysis;

• Work with climate datasets from diverse sources and models (i.e. Copernicus, WorldClim, TerraClimate) under guidance, learning how to process and interpret them for agricultural analysis;

• Run and interpret machine learning and statistical models (e.g. GAMs) to understand crop-climate interactions and future climate impact on crop production;

• Help compile and organize data from diverse datasets, including climate models, satellite imagery, and agronomic data, to enhance the accuracy of predictions;

• Contribute to systems thinking methodologies to analyze interactions, feedback loops, and emergent behaviors within the targeted systems.

Communication and Outreach:

• Support the communication of research findings by contributing to internal reports, visual summaries, and draft content for presentations or publications;

• Engage with other research teams (business impact modelling) to communicate findings and outputs.

Interdisciplinary Collaboration:

• Collaborate with experts from various disciplines, including ecology, sociology, economics, and policy, to foster a holistic understanding of complex systems.

Continuous Learning:

• Stay abreast of the latest developments in agroclimatology, complexity theory, and plant physiology research;

• Actively seek opportunities for professional development and contribute to building the knowledge base within the organization.

Requirements

Required qualifications and experience

• A Bachelor degree in a relevant field (e.g., Agricultural meteorology, climate science, ecology, environmental science) with minimum 2 years of work experience;

• Proficiency in quantitative and qualitative research methods;

• Strong programming skills for model development (e.g., Python, R);

• Strong working knowledge of GIS;

• Familiarity with climate modeling tools, remote sensing techniques, and relevant software;

• Excellent communication skills and the ability to collaborate across disciplines;

• Ability to work collaboratively in a team environment;

• Ability to communicate complex ideas effectively, verbally and in writing, in English.

Benefits

Terms of employment

This position is a national recruited position based in Hanoi, Vietnam. The initial contract will be for 1 year, subject to a probation period of 2 months, and is renewable depending on performance and availability of resources.

This position is graded at BG06 level, with a minimum basic salary of VND 24,487,062 in a scale of BG01 to BG14 (BG14 being the highest level according to CIAT job classification framework policy). We offer a competitive salary and excellent benefits including but not limited to monthly allowances, insurance, retirement plan, staff training and development, paid time off and flexible working arrangements.

CIAT is committed to fair, safe, and inclusive workplaces. We believe that diversity powers our innovation, contributes to our excellence, and is critical for our mission. Recruiting and mentoring staff to create an inclusive organization that reflects our global character is a priority. We encourage applicants from all cultures, races, colors, religions, sexes, national or regional origins, ages, disability statuses, sexual orientations, marital status, and gender identities. Female candidates are strongly encouraged to apply.

Applications

Applicants are invited to visit https://alliancebioversityciat.org/careers to get full details of the position and to submit their applications. Applications MUST include reference number (RFP300765) – Research Associate (Climate Modeler) as the position applied for. Cover letter and CV should be saved as one document using the candidate’s last name, first name for ease of sorting.

Applications closing date: 17 August 2025

Please note that email applications will not be considered.

Only short-listed candidates will be contacted.

We invite you to learn more about us at: http://alliancebioversityciat.org

Potential interview questions

Added 1 year ago - Updated 1 year ago - Source: alliancebioversityciat.org