Staff Engineer – Modeling
| Company | Takeda |
|---|---|
| Location | Boston, MA, USA |
| Salary | $111800 – $175670 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior |
Requirements
- Bachelor’s degree in Chemical Engineering, Pharmaceutical Sciences, or a related field with 5+ years of relevant industry experience.
- Master’s degree in Chemical Engineering, Pharmaceutical Sciences, or a related field with 3+ years of relevant industry experience.
- Ph.D. in Chemical Engineering, Pharmaceutical Sciences, or a related field with 0+ years of relevant industry experience.
- Strong knowledge and understanding of crystallization process modeling, particle engineering, and polymorph control.
- Strong understanding of population balance models (PBM) for crystal nucleation, growth, breakage, and aggregation dynamics.
- Expertise in transport phenomena and thermodynamics as applied to crystal growth, supersaturation control, and solid-liquid equilibria.
- Experience with commercially available crystallization and particle engineering modeling software, such as gPROMS Formulated Products, Dynochem, or Ansys Fluent.
- Experience with computational fluid dynamics (CFD) modeling for mixing and solid suspension applications, using software like Ansys Fluent, Star-CCM+, or MStar CFD.
- Proficiency in data integration from sensors, controllers, and industrial systems, ensuring real-time process monitoring and model-based control.
- Experience with programming tools such as MATLAB, Python, R, SQL, and adherence to good coding practices for model implementation and automation.
Responsibilities
- Contributes to the design, development, optimization, and scale-up of crystallization and particle engineering processes for synthetic molecule drug substances using process modeling and simulation principles.
- Utilizes advanced process modeling tools, population balance models (PBM), and digital twin functionalities, implementing model-based design of experiments (MBDoE) for process characterization, risk assessment, and control strategy development.
- Develops experimental designs and workflows for model development, validation, and verification, with a focus on crystal nucleation, growth kinetics, polymorphism control, and particle size distribution (PSD) engineering.
- Collaborates with cross-functional teams and external partners to develop and deploy digital twins of crystallization, wet milling, and solid-liquid separation unit operations.
- Partners with Automation, Manufacturing, Process Engineers, and PAT experts to develop modeling and simulation (M&S) solutions that can be deployed across the global organization for in-silico process design, development, and optimization.
- Recommends, justifies, and implements in-silico tools and an ‘in-silico first’ approach for crystallization and particle engineering.
- Authors reports, and peer-reviewed manuscripts, conference presentations.
Preferred Qualifications
- Experience with multivariate analysis (MVA) and Principal Component Analysis (PCA) for crystallization process optimization.
- Knowledge of process analytical technologies (PAT) such as FBRM, Raman, PVM, and UV-Vis for real-time monitoring of crystallization processes.
- Hands-on experience in wet lab crystallization and particle size distribution (PSD) characterization.
- Familiarity with Good Manufacturing Practices (cGMP) and regulatory requirements for model-based submissions.
- Understanding of digital twin applications in process development and scale-up.
- Experience in machine learning (ML) or AI-assisted modeling approaches for process optimization.