Full-Time Modeling Scientist - Agriculture
Syngenta Group is hiring a remote Full-Time Modeling Scientist - Agriculture. The career level for this job opening is Experienced and is accepting Bracknell, United Kingdom based applicants remotely. Read complete job description before applying.
Syngenta Group
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We have an exciting opportunity for a Modelling Scientist to join our Global Data Analytics & Predictive Science Team! Within this role you will create, train and validate predictive models to uncover patterns and deliver new data-driven insights for active ingredient development across R&D functions. You will be asked to interpret the outcome of scientific experiments with the help of mechanistic understanding and machine learning / deep learning approaches. Your work will bring forward our understanding of biological performance in crop protection and guide design, optimization and development of novel crop protection solutions.
Key responsibilities will include:
- Interacting with domain experts to understand scientific questions and identifying modelling opportunities to drive business value;
- Driving strategic business initiatives across Crop Protection R&D by interpreting physical chemistry, biokinetic and environmental data to support decision taking and design laboratory, glasshouse and field trials;
- Guiding technical managers in designing field trials aimed at validating scientific hypotheses and model predictions;
- Working with R&D IT and software developers to improve data-models integration and to deploy applications tailored on shareholders’ needs;
- Monitoring and exploring new modelling approaches, analytical tools and methodologies;
- Engaging with high-priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive field trialing;
- Working with colleagues and external collaborators understanding their complementary capabilities and integrating them into projects and initiatives.
What we are looking for
- Strong foundations in data-driven predictive modelling at postgraduate level (Ph.D. in physics, mathematics or related theoretical sciences);
- Years of experience in the use of the main data-science, -analytics, modelling and visualization Python libraries (Pandas/Polars, SciPy, MatPlotLib);
- Scientific domain knowledge in related fields such as biology, (bio)chemistry, environmental sciences;
- Prior experience in developing models relevant to biological or crop protection outcomes (e.g. ecological modelling, ecotoxicology, environmental fate, epidemiology, disease modelling, PKPD) is a plus;
- Knowledge of data analysis and extracting data insights and new understanding, while communicating scientific and data concepts to specialist and non-specialist audiences;
- Adaptability to different business challenges and data types / sources and to learn and utilize a range of different analytical tools and methodologies;
- Ability to visualize and story-telling with data to communicate results to shareholders with different levels of technical proficiency;
- Analytical problem-solving skills with innovative thinking, while effectively collaborating across diverse teams and managing multiple priorities in a multicultural scientific environment.