Lead Process Modeling Engineer

Still Bright•Kenilworth, NJ

7d•$179,000•Onsite

About The Position

Still Bright is bringing the first viable hydrometallurgical alternative to copper smelting to market at a moment when global copper demand is outpacing supply by historic margins. Our proprietary RACER (Rapid and Complete Electrochemical Reduction) process delivers fast, complete copper extraction while recovering precious and critical co-products, and as a closed-loop system it offers precise control over outputs and radically reduces environmental impact. Backed by top-tier investors including Breakthrough Energy Ventures and Material Impact, our team is moving from pilot execution into the next stages of commercial deployment. As the Lead Process Modeling Engineer II, you sit at the heart of Still Bright's commercial strategy. Reporting to the VP of Commercialization and working in close, regular collaboration with the CTO, you own the digital product of our process, comprised of the paired SysCAD process model/digital twin, our in-house techno-economic analysis (TEA), and the life-cycle assessment (LCA) that rides on it, that turns process decisions into the defensible cost, energy, and recovery numbers that prove Still Bright's value proposition. You own the modeling and TEA architecture end to end: the shared model/TEA/LCA structure, the results-cache and sensitivity/Monte-Carlo framework, and the RACER process basis the models are built on. The lead process modeling engineer will build models to explore process optionality, feedstock variants, co-product routes, and scale-up from lab through demo to commercial.. Finding new methods to advance Still Bright's value proposition is a key expectation of this role.

Requirements

8+ years of experience with process simulation software (SysCAD, or an equivalent plant-simulation tool such as METSIM or HSC)
Demonstrated ability to project process economics from process simulation and process data. Understands that the process model is the physical basis that feeds the TEA, and that it's the TEA — not the process model alone — that produces the outputs used for decision-making.
Deep understanding of industrial chemistry, mass & energy balances, unit operations, aqueous and electrochemical processing, and chemical thermodynamics.
Working understanding of electrochemical unit operations (electrolysis/electrowinning) — Faradaic balances, current/voltage/power, efficiency.
Ability to translate complex engineering simulations into clear, persuasive business cases for customers and investors.
BS or MS in Chemical Engineering, Extractive/Process Metallurgy, or a related engineering field.
A seasoned individual contributor who owns ambiguous builds with minimal direction, ramps quickly, and works transparently in a scale-up environment.

Nice To Haves

Practical experience conducting Life Cycle Assessments to quantify environmental footprints (energy, water, co-product accounting, carbon intensity).
Hydrometallurgy domain experience.
Experience with OLI (or equivalent) thermodynamic modeling.
Experience interacting with mining majors or environmental permitting agencies.
Comfort using AI tools to accelerate data handling, model runs, and reporting automation — much of this automation can be built quickly working with AI.
Experience taking a continuous process to sustained steady-state operation with recycle loops.
PhD in a relevant field, with a focus on process optimization or electrochemical systems.
Proficiency in Python for automating data ingestion between mineralogical databases and process models.
Project financial modeling (NPV/IRR with financing structure, tax, depreciation), to bring the TEA → site-financial-model step in-house.
Spanish or other languages relevant to customer / site work.

Responsibilities

Own and evolve the high-fidelity SysCAD digital-twin and commercial-scale process model architecture. Manage third-party consultants as needed to ensure models accurately reflect the chemistry of our closed-loop system.
Work with the VP of Commercialization to craft customer-specific value propositions. You will transform raw feedstock data into detailed economic and environmental projections.
Lead Techno-Economic Analysis and Life Cycle Assessment work to quantify cost savings and value addition, showing customers RACER economics and environmental impact. Ensure every process-optionality and feedstock configuration is wired into the in-house TEA and subsequent financial model so a model run flows straight through to mine-level economics.
Work directly with the VP of Commercialization to craft customer-specific value propositions, transforming raw feedstock data into detailed economic and environmental projections for global mining companies.
Build and lead a proprietary model that ingests complex mineralogical data and determines the optimized process configuration for a given feedstock.
Model the electrochemical unit operations (electrolyzers, electrowinning) — Faradaic/charge balance, current and power draw, cell sizing, efficiency and degradation — and integrate rigorous aqueous-speciation thermodynamics (OLI Systems or equivalent) for multi-solute electrolyte solubility, precipitation, and impurity behavior.
Reconcile model outputs against lab and pilot data, close mass and energy balances, and build repeatable validation workflows. Own the accuracy standard for the model.
Build the model + TEA/LCA system as maintainable, documented, version-controlled tooling that survives handoffs — including automation (e.g., Python) for data ingestion, scenario runs, and reporting.
Collaborate with the technical team to use modeling results to guide process improvements, keeping Still Bright's technology the most economical solution for copper extraction.
Own the process model and TEA work supporting Still Bright's ongoing grants, and produce the model, TEA, and LCA outputs needed for future grant applications.
Own the modeling priorities and architecture while the Process Modeling Engineer(s) determine how to build and execute each delegated model — reviewing the technical input, risks, and trade-offs they surface. Keep all modeling work transparent, well-documented, and defensible to customers, investors, and regulators.