19 Postdoctoral Fellowship at Forschungszentrum Julich, Germany

This project uses numerical simulations to determine the relative importance of the presence of interstellar objects (ISOs) in the interstellar medium. Specifically, the various formation process, the role of ISOs passing through molecular clouds, taking part in molecular cloud collapse and disc formation. Your tasks in detail:

• Perform scientific work on the research topic, in collaboration with the other SDLAA members
• Cooperate with partners in Dynaverse on relevant adjacent topics
• Present / publish results in collaboration meetings, workshops and conferences and the preparation of project reports
• Develop and apply software tools
• Document software and data according to the FAIR data principles
• Contribute to workshops and training activities

As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and optimization. Together with a dedicated partner from bioinformatics you will first survey pairs of drug discovery application problems and corresponding quantum algorithms, before you focus on promising candidates which are explored in more depth. In particular you will work on

• the extension, development and analysis of new quantum algorithms for near-term and fault tolerant quantum computers for drug discovery
• investigating potential quantum advantage of such algorithms in real-world scenarios (in particular in collaboration with the project partners from bioinformatics)
• the estimation of quantum computing resources for the proposed solutions
• the development of quantum algorithms for the efficient input and output of data sets as they occur in drug discovery
• leading contributions to technical reports and scientific articles
• the supervision of PhD and master students

This postdoc position at IET-3, Forschungszentrum Jülich is part of the new multidisciplinary consortium QT-Batt gathering experts from 4 different Helmholtz Centers to implement and deploy integrated methodologies at the cross-section of battery and quantum technologies.
Quantum computing bears tremendous potential in the simulation of interactions and reactive processes in materials with multicomponent composition. You will play a pivotal role in this undertaking, developing core quantum-computing methods and methodical interfaces for integration into a larger framework of quantum technologies for batteries.
Your tasks in detail:

• Develop innovative quantum computing approaches for the simulation of electrochemical processes in complex electrode materials
• Connect quantum-enabled models of reactive phenomena to multiscale battery descriptions within the interdisciplinary consortium
• Validate computational predictions against experimental results to address topical questions for battery materials in collaboration with project partners
• Publish results in impactful journals and present on international conferences
• Contribute to project management activities and the supervision and teaching of students

You will collaborate closely with experimental and theoretical partners in computational materials science, battery research, and quantum software and hardware, forging connections within a dynamic network of experts from across various research centers in Germany. Forschungszentrum Jülich will thereby provide you with unique access to quantum computing hardware—directly on campus!

This postdoc position with a duration of up to three years is available at the IMD-1, at Forschungszentrum Jülich as is part of the new multidisciplinary consortium QT-Batt gathering experts from 4 different Helmholtz Centers to implement and deploy integrated methodologies at the cross-section of battery and quantum technologies. QT-Batt is a pioneering initiative with the ambition to leverage quantum computing and quantum sensing technologies for the development and optimization of next-generation batteries.
Quantum computing bears tremendous potential in the simulation of interactions and reactive processes in materials with multicomponent composition. You will play a pivotal role in this undertaking, developing core quantum-computing methods and methodical interfaces for integration into a larger framework of quantum technologies for batteries.
Your tasks in detail:

• Develop quantum computing approaches for mechanical properties of battery material
• Incorporate inhomogeneous stress effects on the particle and sub-particle level into hierarchical pseudo-2D descriptions of batteries
• Link continuum descriptions to quantum computing accelerated atomistic approaches in an interdisciplinary environment and benchmark against experimental investigations
• Publish results in impactful journals and present on international conferences
• Contribute to project management activities and the supervision and teaching of students

You will collaborate closely with experimental and theoretical partners in computational materials science, battery research, and quantum software and hardware, forging connections within a dynamic network of experts from across various research centers in Germany. Forschungszentrum Jülich will thereby provide you with unique access to quantum computing hardware — directly on campus!

• Responsible scientist for the operation of the X-ray photoelectron spectroscopy (XPS) device
• Upgrade and development of the device for future projects
• Research on fusion relevant materials regarding composition and functionality
• Collegial cooperation on present topics and development of new projects in the field of material research for fusion applications
• Participation in international conferences (including presenting your research results) and preparation of scientific publications with Peer-Review

The project focusses on Tans-Neptunian objects. The key objective is to develop ML tools that provide a quantitative assessment for the quality of fit between observed properties of Trans-Neptunian objects for the various suggested theoretical models. The developed workflow should also be applicable to the other discovery science projects in Dynaverse. Your tasks in detail:

• Perform scientific work on the research topic, in collaboration with SDLAA members.
• Cooperate with partners in Dynaverse on relevant adjacent topics.
• Prepare and publish results in collaboration meetings, workshops and conferences and the preparation of project reports.
• Develop and apply software tools.
• Documentations of software and data according to the FAIR data principles.
• Contributions to workshops and training activities.

As a postdoctoral researcher, you will take on a central role in advancing and integrating the research approaches within CrowdING. You will work closely with two doctoral researchers who focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute to scientific coordination within the project. Your tasks will include:

• Further development and integration of quantitative approaches for analyzing crowd dynamics
• Scientific support and, where applicable, co-supervision of two doctoral projects
• Development of your own research ideas at the interface of modeling, data analysis, and social-psychological concepts
• Collaboration in the planning, implementation, and evaluation of crowd experiments
• Publication of research results in international journals
• Presentations at international conferences and participation in project workshops in Wuppertal and Groningen (NL)
• Exchange and close collaboration with partners from physics, computer science, and social psychology

• Master`s degree with PhD in physics, chemistry, materials science, chemical engineering, or a related discipline
• Strong background in X-ray methods; experience with synchrotron or neutron methods and/or instrumentation is highly desirable
• Knowledge of catalysis and energy storage materials, and interest in operando characterization
• Experience with programming / scripting (ideally Python), and, optionally, with control systems (SPS/PLC, EPICS, Tango)
• Fluent in written and spoken English
• Very independent and self-motivated way of working but also excellent teamwork skills
• High motivation to take on responsibility, lead projects and develop new research directions
• Willingness for international travel and extended research stays at partner facilities

This work will be performed as part of an agile team unified by a common goal: An Industry partner from semen production provides fresh sperm cells and pre-analysis. A second industry partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab). These collaborations enable practically relevant and breakthrough results.
This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital twin of sperm motility, and utilize it to develop a separation method. Your tasks will include:

• Performing computer simulations and matching them to experimental data
• Very close collaboration with experiments, including occasional wet lab work
• Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team.
• Participation in conferences in Germany and abroad (incl. presenting your research results)
• Travel to industry partners to learn and set up on-site research
• Preparing scientific publications and project reports

This work will be performed as part of an agile team unified by a common goal: An Industry partner from semen production provides fresh sperm cells and pre-analysis. A second industry partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal experiments group (You+Supervisor+support by lab). These collaborations enable practically relevant and breakthrough results.
This team goal requires initially videomicroscopy of X-Y fluorescently labeled sperm cells to develop a quantitative model. Once established, predicted separation mechanisms need to be tested.You will perform these experiments.
Your tasks will include:

• Adapt existing DNA labeling protocols to our Workflow
• Performing microscopy experiments on sperm dynamics under various controlled environmental conditions
• Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team
• Testing proposed separation techniques
• Participation in conferences in Germany and abroad (incl. presenting your research results)
• Travel to industry partners to learn and set up on-site research
• Preparing scientific publications and project reports

• Master`s degree with PhD in physics, chemistry, materials science, chemical engineering, or a related discipline
• Extensive knowledge of X-ray methods
• Knowledge of synchrotron science
• Knowledge of catalysis a
• Experience in energy storage
• Experience with programming languages (ideally Python), SPS controls system
• Fluent in written and spoken English
• Very independent and self-motivated way of working but also excellent teamwork skills
• High motivation to take on responsibility and develop own research ideas
• Willingness for regular business trips

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoc – Molecular Machine Learning with Foundation Models

Deadline : Open Until Filled

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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.
Key activities can include:

• Demonstration and experimental characterization of spin coherence during shuttling
• Shuttling-compatible demonstration of high-fidelity qubit control
• Demonstration of T-Junctions (Fig. 1(b)) as step towards qubit grids
• Advancement of a shuttling based architecture with 2D-connectivity
• Migration to industrially fabricated devices