The qFLOW project (Helmholtz Quantum Use Challenge) is recruiting postdoctoral researchers to work on quantum and hybrid quantum–classical algorithms for PDE- and ODE-based models arising in fluid dynamics and environmental systems.
The project focuses on algorithmic development rather than quantum advantage demonstrations on large-scale applications. Current research directions include variational quantum algorithms (e.g. QITE/VarQITE), quantum lattice Boltzmann methods, quantum-inspired tensor network approaches for PDEs, and physics-informed machine learning with exploratory links to QML. Application testbeds come from groundwater hydrology and multiphase fluid dynamics.
qFLOW is a collaboration between Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Centre for Environmental Research (UFZ), Deutsches Elektronen-Synchrotron (DESY), and Forschungszentrum Jülich (FZJ), with access to HPC infrastructure, GPU-based quantum emulation, and quantum hardware (IBM Quantum, JUNIQ).
