QSAR Modeller

Syngenta; Bracknell; On-site; GBP 40,000 - 65,000; Full time

Job summary

Syngenta is seeking a QSAR Modeller to enhance agricultural innovation through advanced modeling techniques. Working at Jealott's Hill International Research Centre, you will provide support in cheminformatics and machine learning to drive the development of safe and effective active ingredients. The role includes building predictive models and collaborating with diverse teams to ensure data quality and model integrity. Join a leading company in the sector and contribute to impactful work in a supportive and inclusive environment.

Benefits

Generous pension scheme

Bonus scheme

Private medical & life insurance

Up to 31.5 days annual holiday

Stimulating campus environment

Access to training and development

Qualifications

• Understanding of chemical structure and properties.
• Experience in predictive machine learning-driven modelling.
• Ability to communicate across functional boundaries.

Responsibilities

• Building predictive models relating chemical structure to relevant endpoints.
• Managing and interpreting outputs from models.
• Communicating model development and use to end users.

Skills

Cheminformatics

Machine Learning

Data Analysis

Statistical Methods

Communication

Education

PhD in cheminformatics, chemistry, or related field

Tools

R

Python

Job description

Company Description

Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. 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. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture!

Job Description

We have an exciting opportunity for a QSAR Modeller to help drive the invention of safe and sustainable active ingredients through QSAR modelling, AI, and data analytics. Within this role you will focus on providing QSAR, cheminformatics and machine learning modeling support to Crop Protection R&D, helping teams to identify high quality compounds with the right balance of properties and inform chemical design and testing strategies. Key responsibilities will include:

• Building predictive models relating chemical structure and/or properties to endpoints relevant for agrochemical research (particularly human safety, human exposure, environmental fate, environmental exposure and ecotoxicology.
• Liaison with functional representatives to understand data and modelling requirements and integrate this into plans for delivery, with interrogation and curation of data for model building.
• Managing and interpreting outputs from models including specification, problem solving, reporting and interpretation for deployment to end users.
• Communicating of model development, use and limitations to a wide and varied community of end users.
• Seeking out latest developments in computational technology and in consultation with senior technical experts assesses their potential use to support early stage research.
• Giving presentations to support the scientific credibility.

Qualifications

What we are looking for?

• A PhD or equivalent experience in cheminformatics, chemistry, or a related field.
• Understanding of chemical structure and properties, and an ability to identify the relevant considerations for a particular endpoint.
• Knowledge of applied statistical methods for data analysis (univariate and multivariate methods).
• Experience in predictive, machine learning-driven modelling (such as multiple linear regression, SVM, random forest, neural networks etc.).
• Experience with R and/or python essential.
• Ability to communicate across functional boundaries.
• Prior knowledge in Large Language Models, toxicology, or environmental safety of chemicals would be beneficial.

Additional Information

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.
• Up to 31.5 days annual holiday.
• Campus environment.
• A position which contributes to valuable and impactful work in a stimulating and international environment.
• The chance to work with and learn from highly qualified and experienced employees.
• Learning culture and wide range of training options.

Syngenta has been ranked as atop 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: https://www.syngenta.com/careers/working-syngenta/diversity-and-inclusion

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.