Staff Engineer – Modeling and Simulations

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Job Description

OBJECTIVE:

Synthetic Molecule Process Development (SMPD) is responsible for the development of robust and cost-effective processes for the manufacture of new small molecule pharmaceuticals, along with methods for achieving and controlling high standards of purity and quality.

The Staff Engineer – Modeling & Simulation will play a key role in bridging process chemistry and process engineering modeling efforts, to design and optimize efficient, scalable, and sustainable reaction processes. This role will focus on kinetic modeling, mechanistic understanding, and use computational tools to guide route selection, optimize reaction conditions, and mitigate impurity formation. The candidate will work in a highly cross-functional environment, supporting both early and late-stage pharmaceutical process development.

ACCOUNTABILITIES:

• Kinetics & Mechanistic Studies: 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.

• Reaction Kinetics & Modeling: 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.

• Computational Chemistry & Simulation: Utilize DFT, Molecular Dynamics (MD), and kinetic modeling to rationalize mechanistic hypotheses, predict reaction pathways, and accelerate process development.

• Process Optimization & Scale-up: Apply first-principles kinetic models to guide process optimization, ensuring robust and scalable reaction conditions.

• Model-Based Experimentation: Design targeted experiments to validate kinetic models and refine reaction mechanisms, reducing empirical trial-and-error.

• Modeling for Route Scouting: Use kinetic and computational insights to assess new synthetic routes, ensuring efficiency, safety, and sustainability.

• Digital & Data Science Integration: 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).

• Cross-functional Collaboration: 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.

EDUCATION, EXPERIENCE AND SKILLS:

Education and Experience:

Required:

• 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