Master Thesis in Quantum-Assisted Optimization of Resource Allocation regarding Product Potentials

Our team identifies relevant technological innovations from science, research and technology partners in order to make them usable for the product teams at an early stage. For this reason, we participate in research projects as an industry partner in areas such as quantum computing in the BMWK project QuaST.
Quantum Computing is a novel, disruptive technology with the potential to tackle challenging optimization problems. These arise in many areas of interest – logistics, network problems, robustness verification. You will research the applications of current noisy intermediate-scale quantum (NISQ) devices and algorithms for optimization use cases.

These are the tasks:

• The specific task is about portfolio optimization regarding the product portfolio of DATEV using a quantum walk-based technique referring to the Markowitz model.
• The outcome should indicate the (order of) products with higher potential for ROI over the low potentials to show in which products the resource and budget allocation is more beneficial.
• A close collaboration with Fraunhofer IKS is intended.

Skills:

• You would like to do your master's thesis in physics, computer science or a related field.
• Basic knowledge in quantum computing
• Basic knowledge in mathematical optimization and/or machine learning
• Programming skills (preferably Python, Qiskit or Pennylane)
• Interest in applied research and the transfer of state-of-the-art methods to relevant applications