Protein Design Team Lead

Role purpose

Lead the development and application of computational protein design capabilities within the Bioinformatics group to support Seeds R&D in China. The role is responsible for growing a team and advancing technical capabilities that enable the discovery, engineering, and optimization of proteins for agricultural applications. Working closely with trait discovery scientists, molecular biologists, breeders, and digital partners, the Protein Design Team Lead will translate biological challenges into innovative protein engineering solutions that accelerate the development of insect control, herbicide tolerance, disease control, genome editing, abiotic stress tolerance, yield enhancement, and other next-generation trait technologies.

Accountabilities

• Team Leadership & Capability Development. Recruit, mentor, and lead a high-performing team of protein design scientists and computational biologists. Establish technical standards, best practices, and reusable workflows that advance capabilities in protein engineering, structural biology, machine learning, and computational design. Foster collaboration across China and global Bioinformatics teams to support long-term Seeds R&D objectives.

• Protein Design & Engineering Innovation. Lead the development and application of computational approaches for protein discovery, engineering, and optimization. Apply advances in protein sequence analysis, structural biology, machine learning, and generative design to create innovative solutions supporting insect control, herbicide tolerance, disease control, genome editing, and other biotechnology and breeding objectives.

• Design Platforms, Workflows & Computational Methods. Establish and maintain scalable protein design workflows and computational platforms that support sequence analysis, structure prediction, protein engineering, design prioritization, and candidate evaluation. Continuously assess and implement emerging technologies that improve the efficiency and success rate of protein discovery and optimization programs.

• Trait Pipeline & Experimental Integration. Partner closely with trait discovery scientists, molecular biologists, breeders, and the Omics Core Lab to translate agricultural challenges into tractable protein engineering objectives. Establish iterative design-build-test-learn workflows that integrate experimental data, enabling continuous
• refinement of protein designs and accelerated delivery of candidates into the Seeds pipeline.

• Cross-Functional Collaboration & Scientific Partnerships. Collaborate with Bioinformatics, AI Engineering, Functional Genomics, Traits Digitalization & Genomics, and research teams to integrate protein design capabilities into broader discovery workflows. Develop and maintain productive collaborations with external academic, industrial, and technology partners to accelerate innovation and expand access to emerging scientific capabilities.

• Technology Strategy & Scientific Advancement. Monitor developments in protein engineering, structural biology, artificial intelligence, and computational biotechnology. Evaluate emerging methods, platforms, and strategic partnerships that can strengthen Syngenta's protein design capabilities and accelerate the development of next-generation agricultural technologies.

Knowledge, Experiences & Capabilities

• Knowledge:
  • Strong understanding of protein structure-function relationships, protein biochemistry, protein engineering, molecular interactions, stability, and design principles.
  • Knowledge of computational protein design approaches, structural biology, machine learning, and AI methods applied to protein discovery and optimization.
  • Familiarity with modern protein modeling technologies, including protein language models, generative design methods, and structure prediction tools.
  • Understanding of biotechnology research, biological data analysis, and experimental workflows used to characterize and validate protein function and performance.
  • Basic understanding of plant biology, crop genetics, and agricultural trait discovery is preferred.
• Education and Experience
  • Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Protein Engineering, Biochemistry, or a related quantitative discipline.
  • 5+ years of experience in computational protein design, protein engineering, structural biology, AI for biology, or related scientific research roles, including experience leading technical projects and/or teams.
  • Demonstrated success applying computational methods to protein discovery, optimization, or engineering, with experience supporting experimental validation and design-build-test-learn cycles.
  • Experience working in multidisciplinary environments spanning biology, bioinformatics,

Note: 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, gender identity, marital or veteran status, disability, or any other legally protected status.

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