Senior Scientist II, Pharmaceutical Development – Thermodynamics & AI/ML Applications (all genders) (fulltime, regular)

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

People. Passion. Possibilities. Three words that make a world of difference.

More than a job. It's a chance to make a real difference.

Welcome to AbbVie! As part of an international company with 48,000 employees worldwide and around 3,000 employees in Germany, you will have the opportunity of addressing some of tomorrows unmet medical needs in close collaboration with your colleagues. Are you passionate about improving global health care? Do you want to contribute to improving patients' quality of life through your expertise? In a challenging work environment that offers opportunities of developing and increasing your own skills? Youve come to the right place!

Together, we break through – as Senior Scientist II, Pharmaceutical Development – Thermodynamics & AI/ML Applications (all genders)

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.