<p><strong>Location: </strong>Remote within Europe, with regular presence in Bremen</p> <p><strong>Direct Reports: </strong>None; supervision of students and interns</p> <p><strong>Working Model: </strong>Remote / hybrid.
Regular time on-site in Bremen.
</p> <h2>Mission</h2> <p>Build 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.
Pillar 1 Simulation Engine
This code runs inside optimisation loops and speed decides what is possible.
</li> <li>Maintain and extend the Julia core and its Python interface.
</li> </ul> <p><em>Success Metrics and KPIs: simulation accuracy against measurement, runtime performance, API stability.
</em></p> <p><strong>Pillar 2 Model Learning and Optimisation</strong></p> <ul> <li>Implement parameter inference and model learning from experimental data.
</li> <li>Work on neural-network approaches to PDE solving and equation discovery.
</li> <li>Benchmark against established academic tools and publish the comparison.
</li> </ul> <p><em>Success Metrics and KPIs: benchmark results, methods adopted by the research group, publications.
</em></p> <p><strong>Pillar 3 Research Collaboration</strong></p> <ul> <li>Work with Constructor University faculty on joint research and grant applications.
</li> <li>Supervise graduate students and interns working on the engine.
</li> <li>Contribute to course material on numerical simulation and machine learning for physics.
</li> </ul> <p><em>Accountability: research collaborations initi.