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Constructor TECH seeks a PhD-level researcher to build a high-performance quantum simulation engine. You will own differentiable simulation, advance ODE solvers and optimization, and extend Julia and Python interfaces.
The role includes parameter inference, model learning from data, and exploring neural-network approaches to PDE solving. Collaboration with university faculty and supervision of students are key aspects.
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.
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
Success Metrics and KPIs: simulation accuracy against measurement, runtime performance, API stability.
Pillar 2 Model Learning and Optimisation
Success Metrics and KPIs: benchmark results, methods adopted by the research group, publications.
Pillar 3 Research Collaboration
Accountability: research collaborations initiated and sustained; students productive.
Experience
Skills & Competencies
Education & Languages
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