Syngenta Group: Scientific Expert – Disease Control Computational Biologist (f/m/d) — Stein, AARGAU, Switzerland

About Syngenta Group

Syngenta Group works in agricultural technology and crop-related innovation. Its employer descriptions connect scientific development and crop solutions with helping farmers use resources effectively and improve how crops are grown. Material from its vegetables-and-flowers business also identifies seed breeding for different climates and horticultural needs. Across these activities, the stated business purpose links agricultural production with resource use and environmental concerns, bringing scientific and technological work to practical farming and growing conditions.

The position and its setting

Syngenta Group lists Scientific Expert – Disease Control Computational Biologist (f/m/d) in Stein, AARGAU, Switzerland, under reference 18076826. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Research
• Employment type: Full-time
• Employer listing date: 22 October 2026
• Brands: Syngenta Crop Protection

Responsibilities and work described

• Purpose of the role
• Delivery: scientific leadership for computational and systems-level disease-control biology, accelerating discovery and development of fungicide, biological and integrated crop-protection solutions
• Integration: pathogen, host, crop, environmental, agronomic and multi-omics evidence with AI/ML, bioinformatics and digital phenotyping to generate robust, decision-ready insight from Discovery through Product Support
• Building: reusable capabilities, standards and partnerships while upholding scientific rigor, data integrity, HSE, compliance and responsible-AI standards
• Shape and co-own computational disease-biology roadmaps aligned with project needs, stage plans and portfolio priorities
• Integration: pathogen, host, crop, environmental, agronomic and multi-omics data into mechanistic, network and predictive models
• Design: robust experiments and bioassays that validate computational predictions across laboratory, greenhouse, semi-field and field conditions
• Development: or co-develop AI/ML approaches for disease diagnosis, image-based phenotyping, efficacy prediction, plant/leaf health and phytotoxicity, resistance/risk assessment and experiment prioritization
• Define fit-for-purpose data pipelines from instrument and assay through analysis and decision support, including LIMS/ELN integration
• Building: reusable methods, standards, digital workflows and platforms, driving adoption across Biology and Disease Control
• Delivery: evidence-based recommendations, options, risks and decision points to project teams and governance forums
• Establishment: strategic collaborations and mentor scientists and postdoctoral researchers, while ensuring reproducibility, IP protection, HSE, compliance and responsible use of AI

Essential requirements and candidate background

• PhD with substantial post-PhD experience leading applied and fundamental research at the interface of disease biology and computational/data science
• Demonstrated practical deployment of computational, statistical or machine-learning approaches in biological research
• Recognized scientific authority able to shape research strategy, capability roadmaps and portfolio-relevant decisions
• Track record of external scientific partnerships, publications, presentations, IP or comparable community contribution
• Experience translating complex biological evidence into product-development, regulatory, stewardship or portfolio decisions
• Fluent written and spoken English
• German is good to have

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Work arrangement: On-site
• Advertised location: Stein, AARGAU, Switzerland

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Scientific Expert – Disease Control Computational Biologist (f/m/d) vacancy is not an offer for reference 18076826; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Syngenta Group

Applications follow the official employer page linked below.

Open the official Syngenta Group posting below and match the title and reference 18076826.

Compare your qualifications and experience with the essential conditions for the Stein, AARGAU, Switzerland position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: AI

An AI-related example should make the task and evaluation explicit. Explain the inputs, the system’s intended output and how you checked errors, usefulness or reliability, rather than relying on the model name alone.

Relevant skills

• AI/ML
• AI
• laboratory testing
• assay development
• compliance
• agronomy
• partnership development