VP Simulation & AI

GREEN14•Stockholm, ME

12d•Onsite

About The Position

We are seeking a visionary leader with expertise in AI, high-speed simulation, and real-time optimization for plasma and high-temperature processes. The company, GREEN14, founded five years ago, aims to facilitate Europe's emission-free production of critical raw materials using hydrogen plasma. The role involves leveraging a fully operational plasma reactor for daily experiments, enabling continuous model improvement with real-world data. The company has invested in multiphysics models, internal solvers, and surrogate models, with external expert review, to bridge the gap between process and simulation engineers. The goal is to solve the problem of global industrial companies lacking fast, reliable models to optimize processes for new target outputs.

Requirements

PhD in a relevant field.
Deep experience in areas such as multiphysics modeling, CFD, plasma physics, high-temperature chemistry, numerical methods, or scientific computing.
Understanding of the strengths and limitations of physics-based solvers, surrogate models, and machine learning.
AI is an integral part of how you think about solving complex scientific problems.
Curiosity about new industrial use cases.
Enjoyment of working directly with both modellers and process engineers.
Care about whether what is built actually solves problems customers face every day.
Comfortable explaining complex ideas.
Ability to engage with customers, industrial partners, and the research community.
Willingness to speak up and suggest better approaches when needed.

Responsibilities

Lead or co-lead a small but growing team of experienced engineers working across simulation, physics, and AI.
Own the computational architecture that integrates multiphysics modeling, internal solvers, AI, and high-performance scientific computing.
Oversee the development from high-fidelity physics models and accelerated solvers to surrogate models and real-time process optimization.
Work closely with the process team in a two-way exchange: helping them understand and improve the physical process, while using experiments and reactor data to improve models.
Drive the transition from high-fidelity multiphysics simulation towards fast, trustworthy surrogate models to answer the question: 'What should I change to get the product I want?'
Determine future technical directions, including model development, capability additions, AI value creation, and productization for industrial customers.
Engage with customers, industrial partners, and the research community.
Build both the technology and the team around it as the company scales.
Influence technical architecture, research priorities, and the productization of simulation and AI for industrial customers.
Contribute to building a computational approach that can help engineers understand, optimize, and scale complex high-temperature processes across industries.