Scientific Expert – Disease Control Computational Biologist (f/m/d)

As a world market leader in crop protection, we help farmers to counter these threats and ensure enough safe, nutritious, affordable food for all – while minimizing the use of land and other agricultural inputs. Syngenta Crop Protection keeps plants safe from planting to harvesting. From the moment a seed is planted through to harvest, crops need to be protected from weeds, insects and diseases as well as droughts and floods, heat and cold. Syngenta Crop Protection is headquartered in Switzerland. Health Promotion Switzerland recognizes Syngenta's commitment to the health and well-being of its employees and awards the "Friendly Work Space" label to all its Swiss sites. At Syngenta, employee health and well-being are key to the company Purpose of the role Provide scientific leadership for computational and systems-level disease-control biology, accelerating discovery and development of fungicide, biological and integrated crop-protection solutions. Integrate 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. Build reusable capabilities, standards and partnerships while upholding scientific rigor, data integrity, HSE, compliance and responsible-AI standards. Accountabilities Shape and co-own computational disease-biology roadmaps aligned with project needs, stage plans and portfolio priorities. Integrate 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. Develop 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. Build reusable methods, standards, digital workflows and platforms, driving adoption across Biology and Disease Control. Provide evidence-based recommendations, options, risks and decision points to project teams and governance forums. Establish strategic collaborations and mentor scientists and postdoctoral researchers, while ensuring reproducibility, IP protection, HSE, compliance and responsible use of AI. 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 — Published by Syngenta Group. Apply on the employer's own posting.