Senior Research Associate

Gene Bank & Tropical Forages

The organization

 The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) delivers scientific solutions that harness agricultural biodiversity to sustainably transform food systems and landscapes, improving people's lives. Our solutions address critical global challenges such as malnutrition, climate change, biodiversity loss, and environmental degradation.

Through innovative collaborations, the Alliance generates evidence and integrates innovations to sustainably nourish people, boost prosperity, and conserve the planet. The Alliance is part of CGIAR, a global research partnership for a food-secure future.

About the position

The Gene Bank Program and Tropical Forages Program  is seeking for a Senior Research Associate to provide statistical and analytical support across collaborative, multi-location research initiatives focused on forage evaluation and characterization. The position involves working with diverse and complex datasets generated by multidisciplinary research teams, integrating data from laboratory, greenhouse, and field-based studies to support analysis, interpretation, and evidence-based decision-making.

The position will be based at the Alliance’s Americas Hub in Palmira, Colombia, with availability to travel within and outside the country.

Responsibilities

• Provide advanced statistical support across all phases of project-based research activities, including experimental design, data cleaning, analysis, and multi-environment modeling.
  
• Create mixed models, longitudinal data analysis, multivariate analysis, and spatial data visualization.
  
• Assist and mentor project partners in statistical analysis and data interpretation to strengthen capacity across centers.
  
• Analyze data generated from in vitro fermentation assays and in vivo trials, including digestibility, gas production, methane emissions, biomass yield, and agronomic performance.
  
• Contribute to the development of evidence-based decision frameworks (e.g., ranking matrices and selection criteria) that integrate nutritional value, methane mitigation potential, and agronomic performance.
  
• Coordinate with multidisciplinary teams and external partners to harmonize data workflows, statistical methodologies and standardize analytical protocols, and ensure reproducibility of results.
  
• Support the development and application of statistical models for interpreting complex datasets, such as those from metabolomics, microbiome, and multi-environment trials.
  
• Maintain project databases to store and manage large datasets from multi-center evaluations.
  
• Co-lead the development of scientific reports, technical briefs, and peer-reviewed publications summarizing statistical findings.
  
• Support training and capacity-building activities, including mentoring project partners in statistical analysis, data interpretation, and dashboard use to strengthen analytical capacity across centers.
  

Qualifications and requirements

• Bachelor’s degree in Biostatistics, Statistics, Data Science, Agricultural Sciences, or a related field.
  
• At least one year of experience providing statistical support for research projects, preferably in agricultural, environmental, or life sciences.
  
• Proficiency in R, Python, SAS, and other statistical or machine learning tools.
  
• Knowledge with mixed models, longitudinal data analysis, and data visualization.
  
• Experience working with datasets related to forage evaluation, animal nutrition, agronomic or environmental indicators (desirable).
  
• Advanced proficiency in English (spoken and written) is mandatory, with proven ability to actively participate in technical discussions, lead or contribute to meetings, prepare scientific documents, and communicate effectively with international, multidisciplinary research teams.
  
• Effective communication skills, with the ability to translate complex statistical results into clear messages for both technical and non-technical audiences.
  

Soft Skills

• Strong organizational and planning skills.
  
• Ability to work collaboratively in diverse and interdisciplinary teams.
  
• Attention to detail and commitment to data quality.
  
• Flexibility and adaptability to changing priorities and project needs.
  
• Ability to follow procedures, policies, and research protocols.
  
• Strong organizational and teamwork skills, with the ability to work in a multicultural and multi-institutional environment.