Senior Scientist II, Pharmaceutical Development - Thermodynamics & AI/ML Applications

Senior Scientist II, Pharmaceutical Development - Thermodynamics & AI/ML Applications

AbbVie

Ludwigshafen, Germany

In this role you'll contribute to the design and application of thermodynamics-based and AI/ML-enabled solutions that support pharmaceutical formulation and process development. The role is responsible for translating complex physicochemical and process data into predictive insight, with emphasis on solubility, phase behavior, physical stability, and material interactions relevant to robust product and process design.

Working in a multidisciplinary environment, you`ll develop and apply hybrid modeling approaches that combine first-principles understanding with machine learning methods, ensuring models are scientifically grounded, fit for purpose, and operationally useful. You`ll also develop (in-silico) digital tools and decision-support workflows that enable broader adoption of modeling outputs across development teams.

Make your mark

• Develop and apply predictive models to guide formulation and process development decisions across pharmaceutical programs;
• Apply thermodynamic and quantum mechanical principles to predict key material and product behaviors such as solubility, phase behavior, crystallization, supersaturation, and moisture sensitivity;
• Build and improve models for physical stability, material compatibility, excipient interactions, and process-related performance of drug substances and drug products;
• Create and implement practical tools and workflows using hybrid physics-based and machine learning approaches that integrate mechanistic insight with experimental and historical data;
• Define and execute robust model validation strategies, including uncertainty assessment, applicability domain evaluation, and clear performance documentation;
• Convert complex datasets into actionable insights for formulation selection, risk assessments, experiment prioritization, and overall development strategy;
• Communicate model findings, assumptions, limitations, and recommendations clearly to both technical and non-technical stakeholders while supporting modeling best practices and reproducibility;
• Work closely with thermodynamic modeling experts, internal modeling teams, and laboratory scientists to ensure model development addresses real-world development needs.

Qualifications

This is how you make a difference:

• Advanced degree (PhD) in pharmaceutical sciences, chemical engineering, physical chemistry, materials science, data science for physical systems or related disciplines;
• Strong understanding of thermodynamics and its application to pharmaceutical materials, formulations, and process performance;
• Proven ability to perform quantitative modeling and analyze and interpret physicochemical experimental data;
• Experience using AI/ML for scientific or engineering problems, with focus on data quality, model suitability, and interpretability;
• Ability to combine mechanistic insight with data-driven methods to address real-world development challenges;
• Proficiency in structuring analyses, documenting methods, and presenting conclusions in a business-relevant manner;
• Strong collaboration and professional communication skills for working across cross-functional, technical, and international teams;
• Excellent written and verbal communication skills in English.