Research associate - bioinformatics - rice Research associate - bioinformatics - rice About the position
The position's objective is to contribute to understanding crop genetics and improving important traits by collecting biological data from diverse sources for the RICE program.
The position will be based in the operations center of the Americas, located in the Campus of Palmira, Colombia.
Key Responsibilities
• Curate, analyze and manage biological data in Linux systems from diverse sources, especially NGS data.
• Develop and implement bioinformatics pipelines to clean and preprocess raw data for quality and consistency, e.g., sequence alignment, variant calling and filtering.
• Conduct statistical analyses and develop scripts (Linux, Python, R) for genetic studies, e.g. population structure, phylogenetical analysis and genome wide association studies (GWAS).
• Generate reports and presentations for group discussions and other focal groups.
• Communicate findings effectively to both technical and non-technical stakeholders.
• Support training for events in the RICE program.
Qualifications and requirements
• Bachelor's degree in biology or agronomic engineering, with an emphasis in computational biology, biological engineering, biotechnology, or related fields.
• Specialization or master's degree in biotechnology or related fields is a plus.
• Proficiency in programming languages (Python, Shiny, R, Linux) and statistical methods.
• Research experience in genomics and bioinformatics (NGS data, population structure analyses, GWAS) is desirable.
• Ability to communicate effectively and collaborate in an interdisciplinary environment.
• Strong analytical and problem-solving skills.
• Continuous learning mindset and adaptability to new technologies.
• Intermediate English level (oral and written).
Competences & Skills
• Highly motivated, self-starting, and flexible, with a demonstrated interest in data analysis, visualization and interpretation of biological data.
• Strong desire to work in a research program implementing data-driven decision-making, by integrating genotypic and phenotypic data.
• Detail-oriented mindset, with the ability to maintain accurate records and documentation.
• Willingness to learn new research approaches integrating traditional and novel tools.
• Demonstrated ability to work effectively as part of a team with people in a multi-cultural and multidisciplinary environment.
biologia Profesional
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