The Theory Team at QNS is currently seeking two postdoctoral candidates to join our research efforts. One of the positions is focusing on Quantum-coherence of surface spins studied by non-equilibrium transport, where the primary research involves studying individual electron spins localized in atoms or molecules on surfaces, recently recognized as promising solid-state quantum bits (qubits). In this role, you will primarily engage in computational studies to deepen our understanding of the decoherence behavior of these systems, extending existing models, and refining quantum control techniques. Collaboration with experimentalists is a key aspect, as you'll work together to implement fundamental quantum algorithms in customized spin systems.

The second position deals with ab initio based design of spins-on-surfaces quantum systems. In this project, we explore the potential of individual electron spins in atoms or molecules on surfaces as solid-state quantum bits (qubits). The research objective centers on utilizing ab initio calculations to uncover new material systems with favorable properties and enhancing existing systems to establish long-lived coherent surface spin states. This role offers a distinctive opportunity to optimize current systems, and actively contribute to the exploration of novel materials, ultimately advancing the field of quantum technologies.

Requirement

• Ph.D. in Physics, Chemistry, or related areas

• English at professional work level

• Interest in working closely with colleagues from theory and experiment in a dynamic environment

Preferred experience

A) Computational studies of quantum spins on surfaces

• Confidence with Fortran or another programming language with focus on implementing physical models in code

• Familiar with open quantum systems

B) Ab initio based design of spins-on-surfaces quantum systems 

• Confidence with density functional theory codes (Quantum Espresso, VASP, etc.)

• Experience in the study of localized magnetism and strongly correlated electron systems

• Knowledge in workflow tools (e.g. ASE, Aiida) and data analysis in python are of advantage