QSAR Team Leader

Overview

As a Scientific Leader in (Q)SAR modelling, you will steer Syngenta’s global strategy for QSAR and expert-knowledge rule-based systems to support data-driven toxicology decisions. You will lead a dispersed team of computational and regulatory toxicologists and ensure regulatory-aligned, defensible read-across and analogue assessments. You’ll apply deep mechanistic chemistry to evaluate structures, fate, and modes of action, shaping risk decisions and techno-regulatory strategies. This role blends science leadership with cross-geography collaboration to advance crop safety and product stewardship.

Pay / Benefits

• generous pension scheme
• bonus scheme
• private medical & life insurance
• up to 31.5 days annual holiday
• learning culture and training options
• international environment

Responsibilities

• Lead a toxicology team responsible for QSAR assessments, driving methodological innovation and testing paradigms.
• Collaborate with global teams to design fit-for-purpose toxicology approaches aligned with regulatory needs.
• Act as an expert resource for regulatory challenges and strategic technical guidance.
• Proactively manage issues in study delivery and stakeholder relations.
• Ensure timely, cost-effective, high-quality toxicology data delivery with strong technical leadership.
• Contribute to innovative techno-regulatory strategies and science-led positions for stakeholders.
• Support training and development within Product Safety, promoting company purpose and leadership model.

Key requirements

• Degree in a scientific discipline relevant to chemistry or toxicology with mechanistic chemistry foundation
• Proven track record in effective technical or people leadership of technical staff
• Ability to manage complexity and ambiguity with internal and external stakeholders (including CROs)
• Capability to comply with regional and global requirements and standards
• Proven ability to contribute innovation to problem solving and emerging toxicology science

• Stakeholder management
• Collaborative leadership
• Strategic thinking
• QSAR modelling
• Expert knowledge/rule-based prediction systems
• Mechanistic chemistry

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