Staff Engineer – Modeling and Simulations

Staff Engineer – Modeling and Simulations

Requirements

• A Ph.D. in Chemical Engineering, Chemistry, or a related field with 0+ years of academic, post-doctoral or pharmaceutical industry experience; an M.Sc. degree in Chemical Engineering, Process Engineering, or a related field with 6+ years of pharmaceutical industry experience.
• Expertise in reaction kinetics, mechanistic modeling, computational chemistry, DFT and kinetic/microkinetic simulations.
• Strong background in experimental kinetics, including in situ reaction monitoring (NMR, mid-FTIR, calorimetry), kinetic parameter extraction (RPKA, VTNA), and mechanistic analysis.
• Experience building kinetic models using tools such as gPROMS, Aspen, ReactionLab, Dynochem, MATLAB, Python, or similar platforms.
• Ability to work in the lab to generate high-quality kinetic data for model development and verification.
• Understanding of process scale-up and application of reaction engineering principles to ensure robust, efficient, and scalable manufacturing processes.

Responsibilities

• Design and execute data-rich experiments using in situ tools (e.g. NMR, mid-FTIR, calorimetry) and offline analytical techniques to track reaction progress and formation of intermediates.
• Extract kinetic parameters e.g., Reaction Progress Kinetic Analysis (RPKA) and Variable Time Normalization Analysis (VTNA), and develop mechanistic kinetic models to quantify reaction kinetics, catalyst behavior, and impurity formation pathways.
• Utilize DFT, Molecular Dynamics (MD), and kinetic modeling to rationalize mechanistic hypotheses, predict reaction pathways, and accelerate process development.
• Apply first-principles kinetic models to guide process optimization, ensuring robust and scalable reaction conditions.
• Design targeted experiments to validate kinetic models and refine reaction mechanisms, reducing empirical trial-and-error.
• Use kinetic and computational insights to assess new synthetic routes, ensuring efficiency, safety, and sustainability.
• Work with process modelers, data scientists, chemists and engineers to integrate kinetic models into digital workflows (e.g., reaction databases, AI-assisted process design tools).
• Act as a technical liaison between process chemistry, engineering, and modeling teams, ensuring effective translation of mechanistic insights into process decisions.
• Responsible for authoring relevant sections of regulatory documents, reports and peer reviewed manuscripts.

Preferred Qualifications

• Experience with data-driven modeling, multivariate analysis, and AI/ML applications in reaction engineering.
• Strong technical communication skills, with experience in cross-functional collaboration and presenting at scientific conferences.