We're looking for an experienced process scientist or engineer with a strong foundation in first-principles modeling and chemical engineering to accelerate how we scale products and evaluate process changes across R&D and manufacturing. You will build and validate mechanistic and hybrid models that capture the physics of our materials and processes enabling faster, smarter decisions from pilot through full-scale production. This role sits at the intersection of engineering fundamentals, computational modeling, and real-world manufacturing impact.

As a senior individual contributor, you'll lead the development of process models that simulate, predict, and de-risk scale-up, reducing our reliance on trial-and-error and compressing the time from formulation to production. You'll work closely with process engineers, R&D scientists, and our data science team to connect physics-based understanding with data-driven approaches, building toward hybrid models and digital twins that can be deployed across our manufacturing network.

We're building new capabilities and we want people who are energized by that. Beyond building models, you'll help define how process modeling is practiced across the organization by establishing scalable methodologies, reusable simulation frameworks, and best practices that raise the bar for how we design, optimize, and transfer processes. This is an opportunity to do technically deep, high-impact work while shaping how modeling and simulation are applied in a materials and manufacturing environment.

Key Responsibilities

Process Modeling & Simulation

• Develop and validate first-principles and mechanistic models for key unit operations and process systems, capturing the physics of heat transfer, mass transfer, fluid dynamics, and reaction/dissolution kinetics relevant to our materials and processes.

• Build process flowsheet models using tools like Aspen Plus to simulate end-to-end process behavior and evaluate the impact of process changes, new formulations, and equipment configurations.

Scale-Up & Process Transfer

• Lead modeling efforts that bridge pilot-scale experiments to manufacturing-scale operations by identifying scale-dependent risks, informing equipment selection, and defining operating windows.

• Develop scale-up and scale-down frameworks that reduce experimental cycles and accelerate the path from product development to production readiness.

• Work with the Engineering Technology Center to test and adopt your models into process R&D.

Hybrid Modeling & Digital Twin Development

• Partner with the data science team to integrate first-principles models with data-driven approaches, building hybrid models that combine physical understanding with empirical learning.

• Contribute to the development and evolution of digital twins for critical process systems, supporting prediction, optimization, and what-if scenario analysis across the manufacturing network.

Analysis, Visualization & Decision Support

• Translate complex simulation outputs into clear, actionable engineering recommendations that inform R&D direction, process design, and manufacturing decisions.

• Develop compelling visualizations and technical narratives that enable cross-functional teams, from scientists to plant leadership, to quickly understand and act on modeling insights.

Methodology, Standards & Capability Building

• Establish scalable modeling methodologies and reusable simulation workflows that can be applied across products, processes, and manufacturing lines.

• Act as a technical resource on process modeling best practices by mentoring team members, guiding analytical approaches, and elevating how modeling is used to support decision-making across the organization.

• Stay current with emerging tools, methods, and computational approaches in process simulation, multiscale modeling, and hybrid/digital twin frameworks.

Qualifications

Education

• Bachelor's degree in Chemical Engineering, Mechanical Engineering, Materials Science, Polymer Science, Physics, or a related technical field; Master's or PhD strongly preferred

Experience

• 5+ years applying process modeling, simulation, or computational engineering to real-world problems in materials, chemicals, polymers, or related manufacturing environments

• Track record of building mechanistic or first-principles models that informed scale-up decisions, process design, or operational improvements - from model development through validation and deployment

• Experience bridging pilot-scale and manufacturing-scale operations, with a practical understanding of how process physics changes across scales

Technical Skills

• Strong proficiency in process simulation tools such as Aspen Plus, Aspen HYSYS, gPROMS, or equivalent flowsheet modeling platforms

• Solid foundation in transport phenomena, thermodynamics, reaction/dissolution kinetics, and fluid dynamics as applied to process modeling

• Experience with CFD or finite element analysis tools (e.g., ANSYS Fluent, COMSOL Multiphysics, Star-CCM+) for unit operation or equipment-level modeling

• Proficiency in Python for custom model development, data analysis, and automation of simulation workflows

• Experience developing or contributing to hybrid models that integrate physics-based and data-driven approaches (preferred)

• Familiarity with digital twin concepts, reduced-order modeling, or model deployment in operational environments (preferred)

• Familiarity with statistical methods, design of experiments (DOE), and uncertainty quantification as applied to model validation and process characterization (preferred)

• Experience with version control (Git) and reproducible computational workflows

Who you are

• Strong communicator who can translate complex simulation results into clear engineering recommendations for scientists, process engineers, manufacturing teams, and leadership

• Comfortable operating in ambiguous, cross-functional environments and taking ownership of high-impact problems without waiting for direction

• Self-directed senior IC who leads through technical credibility by shaping modeling approaches, driving alignment across teams, and raising the bar for how process knowledge is captured and reused

• Energized by continuous learning and staying at the forefront of process modeling, simulation, and computational engineering

Additional information

Applicable only to applicants applying to a position in any location with a pay disclosure requirements under state or local law:

• The compensation range that is described below is the possible base pay compensation that the company believes in good faith that it will pay for this role at the time of posting based on job grade for the position. Individual compensation within this range is based on many factors such as years of experience etc. so the company might pay more or less than the posted range and it is understood that this range may be modified in the future.
• In addition to base compensation, MonoSol provides a yearly incentive compensation bonus, a profit sharing bonus when eligible, a comprehensive benefits package including medical, dental, vision insurances, short term disability, long term disability, accidental death and dismemberment, term life insurance, voluntary term life insurance, transit flexible spending account (if applicable), employee assistance program, identity theft protection, 401k and paid time off (vacation and sick days)

Compensation range - $130,000.00 - $155,000.00

Incentive Compensation Bonus Target - 10-15%

Paid time off amount - 15 days