Downstream Bioprocess Modeling Lead — Mechanistic Simulations

MSD; Boston (MA); Hybrid; USD 142,000 - 224,000; Full time

Benefits offered by this job

Annual bonus

Job summary

Merck in Boston seeks an Associate Principal Scientist to advance mechanistic chromatography modeling across downstream processes. You will build and validate models with CADET/GoSilico, collaborate with DSP and DSCS, and guide scale-up decisions.

You will mentor junior scientists, help shape the modeling roadmap, and contribute to a robust, data-driven decision-making culture in a hybrid work environment.

Qualifications

• PhD in Chemical Engineering, Bioengineering, or related field with 3+ years pharma/industrial experience.
• MS in Chemical Engineering, Bioengineering, or related field with 5+ years pharma/industrial experience.
• BS in Chemical Engineering, Bioengineering, or related field with 7+ years pharma/industrial experience.

Responsibilities

• Build, calibrate, and validate mechanistic chromatography models using CADET or GoSilico.
• Plan calibration datasets for isotherm and mass-transfer parameter estimation.
• Apply models to guide resin and mode selection, gradient and scale-up decisions.
• Extend mechanistic modeling to downstream unit operations such as viral inactivation kinetics, UF/DF.
• Own end-to-end modeling project execution with calibration and validation.
• Mentor junior scientists in mechanistic modeling and simulation.
• Shape the team roadmap and establish modeling standards.

Skills

Analytical Testing

Biochemistry

Chemical Engineering

Molecular Biology

Data Modeling

Modeling & Simulation

Education

PhD in Chemical Engineering / Bioengineering

MS in Chemical Engineering / Bioengineering

BS in Chemical Engineering / Bioengineering

Tools

Cadet / GoSilico

Python

Job description

Merck in Boston seeks an Associate Principal Scientist to advance mechanistic chromatography modeling across downstream processes. You will build and validate models with CADET/GoSilico, collaborate with DSP and DSCS, and guide scale-up decisions.

You will mentor junior scientists, help shape the modeling roadmap, and contribute to a robust, data-driven decision-making culture in a hybrid work environment.