AI/ML Technical Expert – Predictive safety & multimodal biology

AI/ML Technical Expert – Predictive safety & multimodal biology

• Full-time

Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow healthy and nutritious food while taking care of the planet. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision-making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world. Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group.

Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. Regardless of your position, you will have a vital role in safely feeding an ever-increasing population while taking care of our planet. Join us and help shape the future of agriculture.

We have an exciting opportunity for a a scientifically rigorous and innovative AI/ML Technical Expert to advance predictive safety and strengthen early research decision-making through data-driven and mechanistic approaches. Within the role working at the interface of biology, computational science, and artificial intelligence you will translate priority safety questions into robust modelling strategies, interpretable insights, and scalable analytical capabilities. The role will contribute to the development of a predictive safety framework that enables earlier identification of risk, improves mechanistic understanding, and enhances the quality and confidence of decision-making across research programs. Key responsibilities will include:

• Partnering with toxicologists, biologists, chemists, bioinformaticians, and data scientists to define priority questions for predictive safety.
• Leading the development and evaluation of advanced AI/ML methodologies and predictive modelling approaches to address strategic safety questions.
• Applying machine learning, artificial intelligence, statistical modelling, and knowledge-driven approaches to extract meaningful biological signals (such as mechanisms of toxicity, AOPs, and safety-related outcomes) from large, complex, and heterogeneous datasets.
• Translating modelling outputs into actionable scientific insight that supports project and portfolio decisions.
• Evaluating emerging AI, modelling, and computational-biology methods, while identifying applications that offer practical scientific value.
• Communicating complex computational findings clearly and credibly to multidisciplinary audiences.

What we are looking for

• PhD (or equivalent experience) in Computational Biology, Bioinformatics, Systems Biology, Computational Toxicology, Data Science, Computer Science, Biomedical Engineering, or a related discipline.
• Demonstrated experience integrating diverse biological data types and extracting meaningful biological insight from complex, high-dimensional datasets.
• Strong programming skills in Python and experience with modern data science and machine learning frameworks.
• Proven experience in developing, validating and applying AI/ML, statistical, or computational biology approaches to address biological questions, while building reproducible computational workflows, analytical pipelines, and scientific software tools.
• Self-starter with enthusiasm, flexibility and desire to learn and apply new skills.
• Experience in computational toxicology, predictive safety, agrochemical research, pharmaceutical discovery, environmental science, or another applied research setting.
• Familiarity with adverse outcome pathways, mode-of-action frameworks, systems toxicology, network biology, or causal inference.
• Experience with chemical informatics, molecular descriptors, structural alerts, read-across, QSAR, or exposure- and hazard-modelling approaches.
• Background in applying AI to biological or toxicological data, including multimodal learning, graph-based methods, foundation models, or representation learning with experience in using phenotypic imaging, cell painting, transcriptomic, metabolomic, or other molecular data as supporting evidence for model development or mechanistic interpretation.

Our site

Jealott's Hill International Research Centre UK is situated in pleasant semi-rural surroundings between Bracknell and Maidenhead and is the place of work for approximately 800 Syngenta scientists and support staff. Jealott’s Hill is one of the main global research and development sites and key activities include research into discovery of new active ingredients, new formulation technologies, product safety and technical support of our product range.

What we offer

• Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
• 31.5 days annual holiday.
• We offer a position which contributes to valuable and impactful work in a stimulating and international environment.
• The chance to work as part of a global team to address the current and future needs of the agricultural sector and help feed an ever-increasing population.
• A vibrant growth and learning with wide and varied social communities to join and wide range of training options.

Syngenta has been ranked as a top 5 employer and number 1 in agriculture by Science Journal.

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. Learn more about our D&I initiatives here:

Jealott’s Hill has Disability Confident certification.

We are committed to making all stages of our recruitment process accessible to all candidates and our Jealott’s Hill site are a Disability Confident Level 2 Employer. Please let us know if you need any assistance or reasonable adjustments throughout your application and we will do everything we can to support you.

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