ABOUT THE COMPANY:

Climate change, biodiversity loss, environmental degradation, and malnutrition. These four interconnected global crises have put at stake the wellbeing of our planet for years. Fueled by COVID-19, their impact on agriculture, landscapes, biodiversity, and humans is now stronger than ever. Reversing this negative trend is a challenge, but also an opportunity for bold choices and integrated solutions. Established in 2019, the Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) was created to address these four crises, maximizing impact for change at key points in the food system.

JOB SUMMARY

About the position

The Biotechnology program is looking for a Research Associate with strong computational skills and a solid understanding of machine learning, particularly in developing and deploying machine learning models and APIs for data analysis. The ideal candidate will specialize in mechatronics, electronics, biomedical, or a related field, with a focus on artificial intelligence (AI) and a good understanding of plant responses.

The successful candidate will collaborate with our digital agriculture team to develop novel methods for image analysis using advanced machine learning and deep-learning techniques.

The role includes creating and maintaining APIs for data processing and integration with various remote sensing technologies.

This is a unique opportunity to apply and expand your knowledge of AI and machine learning within the context of agricultural technology and plant phenomics.

The position will be based in the operations center of the Americas, located in the Campus of Palmira,

Colombia.

Requirements

Key Responsibilities

·        Machine Learning Model Development: Design and implement machine learning models to analyze data and understand plant responses.

·        API Creation and Maintenance: Develop, test, and maintain APIs for integrating machine learning models and data processing workflows.

·        Data Analysis: Conduct advanced data analysis and visualization, working with large datasets from various image sources.

·        Collaboration with Experts: Work closely with consultants and scientists to develop and refine machine learning models and remote sensing technologies.

·        Field Protocol Development: Support the development of protocols for field data collection and ensure data quality and consistency.

·        Software Development: Participate in developing software tools for data handling, analysis, and visualization.

·        Report Preparation: Prepare monthly reports summarizing research activities and findings.

·        Troubleshooting: Provide technical support for data collection and analysis systems, troubleshooting issues as they arise.

Benefits

Qualifications and requirements

·        Bachelor’s degree in mathematics, mechatronics, electronics, biomedical engineering, or a related field with a specialization in AI or machine learning.

·        Proven experience developing and implementing machine learning models, particularly for image analysis and data processing.

·        Experience creating and maintaining APIs for data integration and analysis workflows.

·        Proficiency in Python and familiarity with digital image processing.

·        Knowledge of plant responses and agricultural systems.

·        Experience in data handling and server storage solutions.

·        Intermediate level of English (oral and written).

Terms of employment 

This is a national recruited position placed at a BG06, on a scale of 14 levels, with level 14 being the highest.

This is a Colombian national search and will be managed through a fixed term contract of a six (6) month period, subject to a probation period according to the local legislation and is renewable depending on performance and availability of resources.

The Alliance Bioversity-CIAT offers a multicultural, collegial research environment with competitive salaries and excellent benefits.

We are an equal opportunity employer, and strive for gender, diversity, and inclusion in our staff, without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, or any other characteristic.

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