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(RFP301254) Research Associate (Climate Data)

Alliance Bioversity & CIAT

Job Location:

Hanoi - Vietnam

Monthly Salary: Not provided by the employer

Experience Required: 1-3years

Posted: 1 June 2026 (30+ days ago)

Application Deadline: 29 August 2026

Vacancies: 1 Vacancy

The job posting is outdated and position may be filled

Job Summary

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 peoples 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

Digital Inclusion team is looking for a skilled Research Associate (Climate Data) to support the agroclimatology team in crop-climate modelling in the Climate Resilience Study. This work will feed into Climate Resilience Platform-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

Contribute to the development and application of statistical and machine learning models to analyze crop-climate interactions climate risks and agricultural productivity trends; Support regional and global agroclimatology research activities by integrating diverse datasets and generating evidence-based insights to improve climate resilience planning and agricultural decision-making;

Engage with internal research teams to communicate modelling approaches analytical outputs and research findings;

Deliver crop analytics and evidence-based insights through desk-based analysis of crop physiology productivity trends and climate sensitivities to support agricultural decision-making;

Deliver integrated agricultural datasets and analytical outputs by processing interpreting and harmonizing data and model outputs from diverse climate agronomic and geospatial sources;

Deliver predictive assessments of cropclimate interactions and future production risks using machine learning and statistical modelling approaches (e.g. GAMs);

Contribute to systems-thinking analyses of interactions feedback loops and emergent behaviors within targeted agricultural systems.

Requirements

Required qualifications experience

Technology career or equivalent in a relevant field (e.g. statistics applied mathematics ecological modelling environmental science economics climate science agricultural meteorology);

At least 2 years of relevant working experience in statistical analysis data modelling or quantitative research;

Experience working with diverse datasets including climate agronomic geospatial or environmental data.

Skills and competencies

Proficiency in quantitative research methods;

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

Nice to have: Familiarity with climate modeling tools GIS 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 BG6 level with a minimum basic salary of VND in a scale of BG01 to BG14 (BG14 being the highest level according to the 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 to get full details of the position and to submit their applications. Applications MUST include reference number (RFP301254) Research Associate as the position applied for. Cover letter and CV should be saved as one document using the candidates last name first name for ease of sorting (Cover letter should illustrate your motivation to apply and suitability for the above position against the listed qualifications and work responsibilities. Detailed curriculum vitae should include the names and email addresses of three professional referees who are knowledgeable about your skills and professional abilities). CIAT collects and processes personal data in accordance with applicable data protection laws.

Applications closing date: 14 June 2026

Only short-listed candidates will be contacted.

We invite you to learn more about us at:

Required Skills:

Technology career or equivalent in a relevant field (e.g. statistics applied mathematics ecological modelling environmental science economics climate science agricultural meteorology); At least 2 years of relevant working experience in statistical analysis data modelling or quantitative research; Experience working with diverse datasets including climate agronomic geospatial or environmental data.

Required Education:

Proficiency in quantitative research methods; Strong programming skills for model development (e.g. Python R); Nice to have: Familiarity with climate modeling tools GIS 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.

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