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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Principal Scientist, Downstream Bioprocess Modeling, Digital Insights - **Company:** Merck Sharp & Dohme LLC - **Location:** Rahway, NJ, United States - **Experience:** Experienced - **Salary:** $142,400.0 - $224,100.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Computer Simulation, Experimental Data, Python (Programming Language), Machine Learning, Data Streaming, Model-Driven Development, Information Technology, Modeling and Simulation, Data Pipelines - **Published:** September 11, 2026 - **Apply:** https://dejobs.org/x/x/A970FC55EA024F10BEB8E1A3AFF5FD44/job/ ## About the Role * Ph.D. in Chemical Engineering, Bioengineering, or a closely-related engineering/physical sciences field with at least 3 years of industrial/pharmaceutical or relevant experience. * M.S. in Chemical Engineering, Bioengineering, or a closely-related engineering/physical sciences field with at least 5 years of industrial/pharmaceutical or relevant experience. * B.S. in Chemical Engineering, Bioengineering, or a closely-related engineering/physical sciences field with at least 7 years of industrial/pharmaceutical or relevant experience. Required Experience and Skills: * Chemical engineering training (or closely related) with deep grounding in preparative chromatography, transport in porous media, and separation science. * Hands-on experience building, calibrating, and validating mechanistic chromatography models in CADET, GoSilico, or equivalent numerical simulation platforms. * Working knowledge of rate models (general-rate, lumped, transport-dispersive) and isotherm formulations (Langmuir, SMA, colloidal/multicomponent variants), and their assumptions and limits. * Practical experience with parameter estimation: designing calibration experiments, fitting isotherms and mass-transfer coefficients, and quantifying identifiability and uncertainty. * Applied understanding of preparative chromatography for biologics (ion exchange, HIC, mixed-mode, affinity), viral clearance, and how column operating parameters translate to product quality and yield. * Track record of applying mechanistic models to real process decisions in resin/mode selection, gradient design, robustness, or scale-up. * Ability to validate simulations against experimental data and to articulate model credibility, sensitivities, and uncertainty to advise action and decision. * Scientific leadership and mentorship experience; comfortable growing modeling capability in others rather than only doing the work personally. Preferred Experience and Skills: * Direct experience in an industrial biologics setting (mAbs, viral vectors, vaccines, or other modalities) as a process development scientist or process engineer. * Experience with mechanistic modeling of adjacent downstream unit operations (viral inactivation kinetics, UF/DF, or depth filtration). * Python fluency for pre-/post-processing, workflow automation, and coupling of mechanistic tools with data pipelines and DOE workflows. * Familiarity with machine learning for downstream modeling: surrogates for expensive mechanistic runs, hybrid mechanistic/ML models, or ML-assisted parameter estimation. * Experience with high-throughput chromatography (HT-PD) or PAT data streams and their integration into model calibration and validation workflows. * Familiarity with continuous / connected downstream processing (multi-column setups, cycle scheduling, dynamic control). * Prior use of mechanistic downstream modeling in technology transfer, process characterization, or troubleshooting at scale. * Prior contributions to technology transfer, process robustness assessments, or troubleshooting using modeling and simulation are a strong plus., Analytical Testing, Analytical Testing, Biochemistry, Cell Line Development, Chemical Engineering, Computer Simulations, Data Modeling Techniques, Detail-Oriented, Downstream Process Development, Downstream Processing, Drug Delivery Technology, Drug Development, Expression Vectors, Interpersonal Relationships, Kinetics, Laboratory Instrumentation, Leading Project Teams, Method Development, Model Development, Model Driven Design, Molecular Biology, Parameter Estimation, Perform Testing, Pharmaceutical Formulations, Pharmaceutical Process Development {+ 9 more}, Valid Driving License ## Description We are seeking an Associate Principal Scientist to join our Process Modeling & Analytics team within the Development Sciences and Clinical Supply Digital Technologies - Digital Insights organization (DDT-DI). Digital is the multiplier that will allow DSCS to deliver better experiments faster, efficient filing and launch, more robust supply chains and higher-confidence decisions across the portfolio. The DSCS Digital Technologies organization is responsible for the invention and application of new digital tools/workflows to support scientists across drug substance development, drug product development and analytical development. We aspire to embed digital technologies into the fabric of DSCS culture to drive transformational impact across the CMC space. In this Associate Principal Scientist role, the successful candidate will apply mechanistic modeling and numerical simulation to downstream biologics processes, with a focus on preparative chromatography and adjacent unit operations. They will build calibrated column and unit-operation models to guide resin and mode selection, gradient and loading strategy, cycle design, filter sizing, robustness assessments, and scale-up decisions across a multi-modality pipeline. The successful candidate will play a technical leadership role in embedding mechanistic downstream modeling into DSCS decision-making-partnering closely with DSP scientists, process engineers, and DS technical leads to translate model outputs into actionable purification and manufacturing decisions. As a senior member of the Process Modeling & Analytics team, they will also mentor junior scientists, help shape the group's downstream modeling roadmap, and grow the practice of mechanistic simulation across the pipeline., * Build, calibrate, and validate mechanistic chromatography models in CADET, GoSilico, or equivalent tools for capture, polishing, and viral clearance steps. * Design isotherm and mass-transfer parameter estimation studies with DSP experimentalists: plan the calibration dataset (breakthrough, gradient elution, tracer runs) needed to identify model parameters. * Apply calibrated models to guide resin and mode selection, gradient and loading strategy, cycle design, pool criteria, robustness assessments, and scale-up decisions. * Extend mechanistic modeling to adjacent downstream unit operations such as viral inactivation kinetics, UF/DF, and depth filtration. * Own end-to-end modeling project execution: problem framing, experimental design for calibration, solver setup, validation against experimental data, and clear communication of predictions and their limitations to cross-functional stakeholders. * Mentor junior scientists on the Process Modeling & Analytics team; grow their technical judgment in mechanistic modeling, numerical methods, and simulation-based decision making. * Shape the team's downstream modeling roadmap and establish practical standards for model development, calibration, validation, and reuse across the portfolio. ## Related Videos - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) ## Related Articles - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Best Companies to Work For in Berlin: Top 14 Companies in 2023 ](https://www.wearedevelopers.com/magazine/188-best-companies-to-work-for-in-berlin-top-14-companies-in-2023)