10 Postdoctoral Fellowship at Forschungszentrum Julich, Germany

Building on in-house fabricated devices, we have recently demonstrated the ability to shuttle electrons between gate defined quantum dots in Si/SiGe over micron-scale distances using only four different AC-voltages, independent of the distance covered https://arxiv.org/abs/2108.00879 . Theoretical consideration indicate good prospects for maintaining spin-coherence of the shuttled electron, which would make this approach very promising for scaling up semiconductor spin qubit devices. This position focuses on experimentally demonstrating coherent spin shuttling, shuttling-compatible high-fidelity qubit control and further ingredients for a shuttling-based architecture, using devices from academic or industrial fabrication.

This position focuses on developing, operating, and characterizing superconducting quantum devices. Your tasks in detail are:

• Development of novel methods for experimentation, fabrication, and characterization
• Develop gate implementations, benchmarking and algorithms
• Work on the interdisciplinary challenges in systems engineering
• Install and improve experimental setups and fabrication tools
• Supervising and guiding Master and PhD students
• Active participation in project meetings and events
• Presenting and publishing the research on an international stage

We are looking for a postdoc to further develop system-based approaches to nuclear verification, possibly building on our earlier work on the topic (e.g. doi:10.1002/nav.21689, doi:10.1007/978-3-030-29537-0). The aim is to better identify the specific challenges of nuclear verification and to draw up solutions and concrete recommendations for action.

In a large collaborative project funded by the Federal Ministry of Education and Research related to hydrogen production, you will:

• Setup and perform large eddy simulation in order to evaluate the impact of local hydrogen production on the ambient atmospheric conditions.
• The simulation results will be analyzed using advanced data analytics technologies to inform the design and planning of hydrogen production at scale.

Quantum computing is a promising, disruptive technology for solving optimization and simulation problems which is at the heart of energy grid design and operation. As part of a large scientific project with renowned partners from the quantum and energy community, you have the opportunity to contribute significantly to the further development of existing or completely new quantum algorithms for energy systems. Your work should first focus on the translation of basic power system algorithms to quantum computing (QC). As a result of this phase, use cases should be defined to highlight the value of QC in energy grids simulation, optimization and control aligned with QC technology development.

Quantum optimization (QO) is a promising, potentially disruptive technology for solving difficult optimization problems which is at the heart of energy system design and operation. While illustrative, energy-related examples (e.g., unit commitment) have been ported onto quantum computers, the potential of QO for energy systems engineering, especially with respect to the design and operation of multi-carrier energy networks, remains largely unknown. Our goal is to identify design and operational problems for which efficient quantum formulations and hybrid quantum-classical algorithms can be derived and to analyze scalability and relative performance of quantum-(assisted) optimization compared to state-of-the-art classical optimization. To this end, we will perform extensive computational experiments on the Jülich D-Wave quantum annealer and on a gate-based quantum computer over the cloud. We are supported by our project partners and quantum computing experts at the Jülich Supercomputing Centre (JSC) and the Peter Grünberg Institute – Institute for Quantum Computing Analytics (PGI-12). Your Tasks in Detail:

• Develop techniques to simulate and control the dynamics of a diamond-based spin system for increasing system complexities
• Find parameter regimes and control schemes to map interesting many-body Hamiltonians on experimentally realizable spin systems
• Cooperate and actively work with experimental partners developing quantum simulators using this technological platform
• Design and implement optimization techniques tailored to experimental constraints

• Development of models for multiphase flow coupled with chemistry (mineral dissolution and precipitation) in porous media
• Implementation of mineral crystallization mechanisms in reactive transport codes operating in high performance computing environments
• Development of surrogate models to speed up geochemical calculations
• Processing of the data and scientific interpretation of the results
• Independent presentation of the results at scientific conferences and in scientific publications

• Development of a computer vision-based pipeline for evaluating the transport and geochemical properties of evolving porous media
• Application of machine learning tools to establish an automated image processing workflow for data evaluation of optical microcopy images and creation of input data for further modelling
• Development of algorithm for identification of crystal morphologies and determination of mineral growth/dissolution rates from optical microscopy images
• Development of surrogate models based on simulated images to derive transport properties of porous media
• Collaborate with other scientist in the team for the development of an assisted geochemical lab on a chip
• Independent presentation of the results at scientific conferences and in scientific publications