Location: Remote within Europe, with regular presence in Bremen
Direct Reports: None; supervision of students and interns
Working Model: Remote / hybrid. Regular time on-site in Bremen.
MissionBuild the simulation and model-learning engine at the centre of Constructor's quantum software. The work is numerics-heavy: differentiable simulation of physical systems, inference of model parameters from experimental data, and optimisation at scale. The role sits between physics and engineering and requires genuine depth in both.
ResponsibilitiesPillar 1 Simulation Engine
- Build and maintain high-performance simulation code for open and closed quantum systems.
- Own the differentiable simulation and automatic differentiation layer.
- Drive performance. This code runs inside optimisation loops and speed decides what is possible.
- Maintain and extend the Julia core and its Python interface.
Success Metrics and KPIs: simulation accuracy against measurement, runtime performance, API stability.
Pillar 2 Model Learning and Optimisation
- Implement parameter inference and model learning from experimental data.
- Work on neural-network approaches to PDE solving and equation discovery.
- Benchmark against established academic tools and publish the comparison.
Success Metrics and KPIs: benchmark results, methods adopted by the research group, publications.
Pillar 3 Research Collaboration
- Work with Constructor University faculty on joint research and grant applications.
- Supervise graduate students and interns working on the engine.
- Contribute to course material on numerical simulation and machine learning for physics.
Accountability: research collaborations initiated and sustained; students productive.
RequirementsExperience
- PhD or equivalent in physics, applied mathematics or computational science.
- Strong scientific computing in Julia, Python, JAX or comparable.
- Real numerical depth: ODE solvers, optimisation, stochastic processes, automatic differentiation.
- Published work, or code that others rely on.
Skills & Competencies
- Able to take a method from a paper and make it fast, tested and usable.
- Comfortable owning code quality, not only correctness.
- Interest in supervising students alongside the engineering.
- Clear technical writing.
Education & Languages
- PhD in physics, applied mathematics or computational science.
- Fluent English.
This role IS
- A research-grade engineering role with a product at the end of it.
- Central to the group's core technical asset.
- A role with a route into teaching and supervision if you want it.
This role is NOT
- A pure research position without delivery.
- A general software engineering role.
- A role where someone else owns the numerics.
Skills Required
- PhD or equivalent in physics, applied mathematics, or computational science
- Strong scientific computing experience in Julia, Python, JAX, or comparable technologies
- Expertise in numerical methods including ODE solvers, optimisation, stochastic processes, and automatic differentiation
- Published work or software code relied upon by others
- Ability to implement methods from research papers as fast, tested, usable software
- Ability to take ownership of code quality and correctness
- Interest in supervising students and interns
- Clear technical writing skills
- Fluent English
What We Do
Constructor Knowledge Labs (CKL) is a research institute based in Bremen, Germany, dedicated to advancing applied research in Computer Science, Software Engineering, Machine Learning, and Artificial Intelligence across interdisciplinary domains.









