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Company Description About Syngenta At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerl…
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Descripción de la empresa Sobre Syngenta Syngenta es un líder mundial en innovación agrícola con presencia en más de 90 países. Nos enfocamos en desarrollar tecnologías y prácticas agrícolas que empoderen a los agriculto…
Senior Research Scientist – Molecular Assay Development
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Senior$4.5B raised
Company Description About Syngenta At Syngenta Seeds Field Crops, we're shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We’re a global Ag Tech powerhouse, headq…
Company Description At Syngenta Seeds Field Crops, we are shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We are a global Ag Tech powerhouse, headquartered in t…
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Descripción de la empresa Sobre Syngenta Syngenta es un líder mundial en innovación agrícola con presencia en más de 90 países. Nos enfocamos en desarrollar tecnologías y prácticas agrícolas que empoderen a los agriculto…
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Company Description Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yields of crop…
Company Description About Syngenta At Syngenta Seeds Field Crops, we're shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We’re a global Ag Tech powerhouse, headq…
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Full-time
postgraduate degree
Posted 2h ago
~40 hrs/week
Responsibilities
Design reusable computational data models and knowledge structures to make scientific R&D information interoperable and AI-ready. Develop ontologies and knowledge graph foundations to enable predictive analytics and advanced AI solutions across the AMEA region.
Requirements
Requires an advanced degree (MSc or PhD) in data science, bioinformatics, or a related field with proven experience in semantic modeling and knowledge graphs. Must possess strong programming skills in Python, R, or SQL and the ability to translate complex scientific domain concepts into machine-readable structures.
Full job description
Company Description
About Syngenta
At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection from seed to harvest.
Job Description
The Computational Data Modeler plays a critical role in strengthening Crop Protection R&D by designing reusable data and knowledge structures that make complex scientific information interoperable, discoverable, and AI‑ready. By translating domain complexity into robust computational models and knowledge foundations, the role enables predictive data analytics, scalable digital products, and next‑generation AI solutions across the region – AMEA & JANZ
Accountabilities:
Data Engineering and Computational Modelling
Design computational data models, reusable schemas, and structured data frameworks that improve interoperability, consistency, and machine usability across the R&D data ecosystem.
Define reusable entity structures, metadata patterns, relationships, and data contracts that support integration across experimentation systems, analytics environments, and digital products.
Translate scientific and business complexity into scalable model logic and reusable data structures that support analytics, digital workflows, and AI-enabled applications.
Context- and Knowledge-Driven Data Modelling
Develop context-rich data models that connect scientific data, metadata, documents, protocols, business rules, and domain concepts into reusable knowledge assets
Create information structures that preserve scientific meaning and operational context to improve consistency across functions and over time
Improve discoverability and reuse by formalizing relationships, definitions, and contextual attributes across fragmented systems and data sources.
Ontology, Knowledge Graph, and RAG Foundations
Apply ontology principles to define consistent concepts, hierarchies, relationships, and machine-readable rules across priority R&D data domains
Support the development of R&D knowledge graph foundations by modeling relationships between experiments, protocols, observations, methods, assets, and decisions
Enable Retrieval-Augmented Generation (RAG) and other knowledge-driven AI approaches by improving retrieval structures, contextual linkages, and connections between structured and unstructured information
AI-Ready Data Platform Enablement
Contribute to AI-ready data platforms by defining reusable knowledge layers, integration patterns, and data-readiness standards
Partner with platform owners, Bioinformatics leads and technical stakeholders to scalable AI integration, and reliable information retrieval
Collaboration with Data Scientists and Bioinformatics Leads
Collaborate with Data Scientists and Bioinformatics lead to ensure analytical, digital, and AI solutions are built on reusable and scalable data foundations
Contribute to shared architecture discussions, design reviews, and foundational modelling decisions aligned with business and platform needs
Documentation, Standards, and Change Enablement
Document modelling standards, ontologies, schemas, and reusable reference patterns to support consistent adoption across teams
Provide technical guidance on computational data models, ontology structures and AI-ready data design approaches
Governance, Safety, and Professional Standards
Ensure data models and knowledge structures align with governance, security, lineage awareness, traceability, and responsible AI enablement standards
Balance architectural rigor, usability, innovation, usability, and practical business value to support scalable implementation
Qualifications
Advanced degree (MSc or PhD) or equivalent applied experience in data science, computational modeling, data engineering, knowledge engineering, computer science, bioinformatics, or a closely related field.
Demonstrated hands on experience designing reusable computational data models, including entities, schemas, relationships, metadata structures, and model driven data consumption patterns.
Strong expertise in semantic modeling, ontology principles, and knowledge representation, with the ability to translate complex domain concepts into machine readable structures.
Proven experience with knowledge graphs, information retrieval, or retrieval augmented generation (RAG)–enabling architectures, including context layering and source grounding.
Solid programming and data engineering capability (e.g., Python/R, SQL), with experience working on modern data platforms and analytics ecosystems.
Ability to translate scientific, business, and operational rules into robust, reusable model logic that supports analytics, digital workflows, and AI enabled applications.
Experience designing for interoperability and reuse across platforms and products, avoiding one off or locally optimized solutions.
Strong communication and collaboration skills, with experience working in matrix environments and explaining complex modeling or architecture concepts in practical business terms
Additional Information
Preferred base location for this role is Bangkok. However, candidates located in other countries within the AMEA region where Syngenta operates may also be considered, depending on business and operational needs.
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.
Join us in our journey as a global agriculture technology leader to feed the world while respecting the earth.
Industry
Farming
Company size
10,001+ employees
Headquarters
Basel, Basel-Town
LinkedIn followers
129,690
Total funding
$4.5B
To help feed 10 billion people while reducing emissions and improve biodiversity. This is our mission as the global agriculture technology leader. With over 50,000 employees in more than 90 countries and hundreds of thousands of agricultural partners worldwide, we are committed to transforming agriculture into a more sustainable, productive system to benefit society and the planet.
We invite you to join us in this collective mission to feed the world while respecting the earth.
Join us in our journey as a global agriculture technology leader to feed the world while respecting the earth.
Industry
Farming
Company size
10,001+ employees
Headquarters
Basel, Basel-Town
LinkedIn followers
129,690
Total funding
$4.5B
To help feed 10 billion people while reducing emissions and improve biodiversity. This is our mission as the global agriculture technology leader. With over 50,000 employees in more than 90 countries and hundreds of thousands of agricultural partners worldwide, we are committed to transforming agriculture into a more sustainable, productive system to benefit society and the planet.
We invite you to join us in this collective mission to feed the world while respecting the earth.