Modelling Scientist (f/m/d)

Purpose of your Job

Our Science and Technology team is looking for a Modelling Scientist to advance data-driven drug development through cutting-edge computational approaches. In this role, you will apply mechanistic models, machine learning, and molecular simulations to predict the stability and behaviour of biopharmaceutical products. You will work closely with cross-functional teams to integrate modelling into experimental workflows and support innovative, model-informed development strategies.

Are you passionate about scientific modelling and pharmaceutical innovation?

Your Responsibility

• Act as a scientific contributor in cross-functional research and development projects, supporting the integration of advanced modelling approaches into biopharmaceutical development.
• Develop, validate, and apply advanced computational models to simulate the physical and chemicals stability, as well as the behaviour, of biopharmaceutical drug products.
• Integrate experimental and structural data into predictive modelling frameworks.
• Utilize a range of modelling techniques, including mechanistic models, machine learning approaches, and molecular simulations, to generate actionable scientific insights.
• Contribute to the development of internal modelling platforms, tools, and workflows to enhance scalability and reproducibility.
• Design and execute simulation studies to investigate formulations parameters, degradation pathways, and process related risks.
• Collaborate closely with cross-functional teams including formulation scientists, analytical experts, and business developers to align modelling strategies with project objectives.
• Analyse and interpret complex data to generate actionable insights.
• Translate and present complex modelling outcomes into clear, impactful recommendations for internal stakeholders and project teams.
• Ensure model quality through rigorous validation procedures and documentation, following internal standards and regulatory expectations where applicable.
• Drive continuous innovation by exploring and implementing state-of-the-art computational approaches relevant to pharmaceutical formulation science.
• Maintain up-to-date knowledge of developments in computational modelling, data science, and biopharmaceutical development to ensure the scientific relevance and competitiveness of modelling approaches.
• Contribute to scientific excellence by co-authoring peer-reviewed publications.
• Support regulatory submissions by providing modelling data and documentation as needed.

What you need to succeed

• Master’s degree or higher in Chemistry, Physics, Mathematics, Engineering, or a related field (PhD preferred)
• Formal training or academic coursework in mechanistic modelling, machine learning, bioinformatics, or molecular dynamics is advantageous.
• 2–5 years of experience in pharmaceutical research and computational modelling, ideally with exposure to protein- and nucleic acid-based therapeutics.
• Strong programming and data analysis skills, with proficiency in tools such as Python, MATLAB, or R, and familiarity with modelling and simulation libraries.
• Expertise in mechanistic modelling, machine learning, molecular modelling, or molecular dynamics simulations.
• Solid understanding of biopharmaceutical products, including structure-function relationships, degradation mechanisms, and formulation challenges.
• Experience in integrating computational models into experimental workflows and interdisciplinary project settings.
• Strong analytical thinking and problem-solving capabilities, with a track record of scientific contributions such as peer-reviewed publications or conference presentations.
• Excellent communication skills, with the ability to translate complex modelling results into clear insights for diverse audiences.
• Fluency in English, both written and spoken.
• Collaborative and team-oriented mindset with a proactive and open approach to interdisciplinary work.
• A passion for scientific innovation, curiosity, and a commitment to staying at the forefront of computational and pharmaceutical science.