08 Postdoctoral Fellowship at Forschungszentrum Julich, Germany
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Forschungszentrum Julich, Germany invites online Application for various Postdoctoral Fellowship in their different Departments. We are providing a list of Postdoc Fellowship positions available at Forschungszentrum Julich, Germany.
Eligible candidate may Apply as soon as possible.
(01) Postdoctoral Fellowship Position
Postdoc Fellowship Position summary/title: Postdoctoral Researcher in Quantum Machine Learning
The mission of the Institute for Quantum Computing Analytics (PGI-12) is to model and improve quantum computing systems on multiple levels. From optimal control of the hardware, over error mitigation and compilation, to application specific quantum algorithms. We focus working on interfaces between disciplines in large innovative projects that strive for the development of scalable and useful quantum computers. In a tight integration with quantum computer hardware developers, we investigate the applicability of quantum computers towards real-world applications in a hardware-software co-design paradigm.
The development of quantum technologies and machine learning are two of the most dynamic research directions of our time. Within the Helmholtz Young Investigator Group “Machine Learning for Quantum Technology” we aspire to merge the parallel advancements of both fields, where quantum challenges match the natural strengths of machine learning and, reversely, the quantum applications call for the development of new machine learning techniques. Therefore, our research targets the exciting intersection of (non-equilibrium) quantum matter, quantum optics, quantum information, and machine learning with the goal of enabling benchmarking and control of quantum devices at the utmost of our computational toolbox. The Young Investigator Group is part of the Peter Grünberg Institute – Quantum Control (PGI-8) at Forschungszentrum Jülich, which specializes in novel optimal control strategies for emerging quantum technologies. Current research directions include tensor network methods, machine learning, in-situ optimal control, and quantum many-body phenomena.
Postdoc Fellowship Position summary/title: Postdoc – Artificial Intelligence in Science
Are you a researcher in science, technology, engineering or math? Have you applied AI techniques in your field? Then it is time to broaden your views. Our AI Consulting Team seeks new applications for AI in science. We team up with researchers from all scientific disciplines and jointly develop innovative approaches to bring their fields forward. At the Jülich Supercomputing Centre (JSC), we operate one of the most powerful supercomputer infrastructures for scientific and engineering applications in Europe. In our lab “Applied Machine Learning”, we develop new ML applications for science. We identify exciting data sets, develop interesting research questions, train powerful models, and try to push further what is possible with AI.
Postdoc Fellowship Position summary/title: Postdoc – ML-Based Image Processing
At the Institute of Energy and Climate Research – Fundamental Electrochemistry (IEK-9), we perform research on highly relevant topics related to the energy transition. For example, we investigate new battery concepts and how we can turn the greenhouse gas carbon dioxide (CO2) to the fuel of the future. In addition to advanced experimental research about the fundamentals of electrochemistry, we also prioritize theoretical simulations and the latest methods of data science in order to facilitate the interpretation of experiments as well as to develop new, digitally supported experimental techniques.The aim is to develop sustainable and cost-effective electrochemical systems with improved energy and power density, longer life time, and maximal safety. Find out more about our mission and future-oriented projects here: https://go.fzj.de/IEK-9
Postdoc Fellowship Position summary/title: Postdoc in the domain of coherent spin shuttling for scaling semiconductor qubits
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.
Postdoc Fellowship Position summary/title: Postdoc in Performance and Degradation Modeling of Polymer Electrolyte Fuel Cells and Electrolyzers
In order to reduce the dependency on fossil fuels, meet targets for CO2 emissions and mitigate resource depletion, it is strategically important to develop economically viable, sustainable and mass-deployable hydrogen-based energy systems. Examples are polymer electrolyte-based fuel cells for heavy duty transport, or electrolyzer cells for hydrogen production. In order to support experimental efforts in the development of energy materials, components, cells and systems, the aim of this postdoc position is to contribute to the development of a physics-based model framework for the prediction of the performance over the lifetime of an electrochemical cell. This framework will enable improvements in design, operation and health monitoring of materials, components and cells. A strategy for model parameterisation, based on advanced diagnostic tools and protocols, will be developed. Guidelines for materials design shall be derived. The work will be part of projects with industry and academic partners. The position offers possibilities for gaining first co-supervision and leadership experiences, coordination of research projects and involvement in planning and development of research programs.
Postdoc Fellowship Position summary/title: Postdoc – Material bottlenecks of the global energy transition
The transformation of our energy system towards greenhouse gas neutrality requires large quantities of materials for the construction of new energy technologies. Among them are critical materials whose availability may be limited due to various constraints. These constraints include geological resources and reserves, geopolitical developments, current and future limits in recycling, and material demand from other sectors of the economy. This can lead to material bottlenecks that could subsequently jeopardize the energy transition. Against this background, your research should focus on the one hand on the future material demand by energy technologies together with a PhD student co-supervised by you and on the other hand on analyzing the availability of primary raw materials as well as the competing material demands of economic sectors beyond the energy system. Here, the following questions, for example, are to be addressed: How much of which primary raw material can be obtained where at what cost? What potential politically induced supply constraints might there be? Which materials are only available as co-products? How does material demand scale with lifetime and plant size? How might future technology developments impact material demand for energy technologies? How does material demand from other sectors of the economy evolve? Your creativity and expertise is needed to answer these questions. The results of your research should be integrated into a holistic open-source material energy system model in order to identify possible future material bottlenecks of the energy transition and options to avoid them. This is ideally compatible with our energy system model FINE: https://github.com/FZJ-IEK3-VSA/FINE
Postdoc Fellowship Position summary/title: PostDoc / Staff Scientist (w/m/d) – Computer Vision for Scientific Imaging Applications
You are a post-doctoral researcher or experienced computer vision scientist and want to make an impact in societally relevant applications by advancing computer vision theory and methods? This is the position for you! The newly founded Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) aims at advancing theory and application of data sciences. Our interests range from use-inspired, method-driven theory to application-driven research. We are looking for a research scientist to join our Computer Vision team, where we focus on three major aspects of computer vision theory and methods relevant for scientific imaging applications: Method adaptation, beyond fully supervised learning as well as Reliability and Quantification. Please find further information below.
Forschungszentrum Jülich is a member of the Helmholtz Association of German Research Centres and is one of the largest interdisciplinary research centres in Europe. It was founded on 11 December 1956 by the state of North Rhine-Westphalia as a registered association, before it became “Kernforschungsanlage Jülich GmbH” or Nuclear Research Centre Jülich in 1967. In 1990, the name of the association was changed to “Forschungszentrum Jülich GmbH”. It has close collaborations with RWTH Aachen in the form of Jülich-Aachen Research Alliance (JARA).
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