AI/ML Technical Expert – Predictive safety & multimodal biology

Syngenta; Stein; Vor Ort; CHF 120.000 - 190.000; Vollzeit

Zusammenfassung

Syngenta invites applications for an AI/ML Technical Expert to advance predictive safety by translating priority safety questions into robust modelling strategies at the nexus of biology and computational science. You will craft scalable analytical capabilities to inform early decision-making across research programs.

Working at Syngenta, you will collaborate with toxicologists, biologists, chemists, bioinformaticians, and data scientists to develop and evaluate cutting-edge AI/ML methods and to

Qualifikationen

• PhD (or equivalent) in Computational Biology, Bioinformatics, Systems Biology, Computational Toxicology, Data Science, Computer Science, Biomedical Engineering, or related field.
• Experience integrating diverse biological data types and extracting meaningful insights from complex datasets.
• Strong programming skills in Python and experience with modern data science frameworks.
• Proven experience developing AI/ML or computational biology approaches with reproducible workflows.
• Self-starter with enthusiasm and willingness to learn.

Aufgaben

• Partner with toxicologists, biologists, chemists, bioinformaticians, and data scientists to define priority questions.
• Lead development and evaluation of advanced AI/ML methodologies for predictive safety.
• Apply ML and knowledge-driven approaches to extract biological signals from large datasets.
• Translate modelling outputs into actionable scientific insights for project decisions.
• Communicate findings clearly to multidisciplinary audiences and evaluate new methods for value.

Kenntnisse

Python programming

AI/ML methodologies

Data analysis

Scientific communication

Ausbildung

PhD inComputational Biology/Bioinformatics/CS

Tools

Python

ML frameworks (TensorFlow/PyTorch)

Data analysis tools

Jobbeschreibung

Company Description

At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection from seed to harvest.

Company Description

At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection from seed to harvest.

Syngenta has been ranked as a top employer by Science Magazine, and it has been awarded with the "Friendly Work Space" label to all its Swiss sites.

Job Description

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.

Qualifications

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.

Desirable Experience

• 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.

Additional Information

What we offer

• A position which contributes to valuable and impactful work in a stimulating and international environment
• A superb working environment with an open culture and diverse workforce where new ideas are always welcome
• The opportunity to work with and learn from highly qualified and experienced employees and gain scientific and technical excellence
• Learning culture (Together we Grow) and wide range of training options
• You will profit from a competitive pension fund plan, flexible working, attractive bonus system, onsite doctor, fitness room, canteen, and other benefits such as Family friendly initiatives, Child and Family allowance

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.