19 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.

• Master or PhD in physics or related with a background in the field of experimental quantum information
• Deep knowledge of solid state physics and/or quantum information
• Experience with microfabrication and/or operating and calibrating quantum systems
• Experience with hardware interfacing programming in Python
• Team-oriented and highly motivated to work in an experimental laboratory
• A background in quantum computing as well as experience with cryogenics, signal delivery, materials optimization, and microwave control are highly preferred qualifications

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 QO formulations for energy system design and operation
• Perform and analyze computational experiments on quantum computing hardware
• Analyze performance and scalability of QO and compare to classical optimization
• Develop hybrid quantum-classical algorithms for mixed-integer and constrained problems
• Closely work together with our project partners and become part of an interdisciplinary team
• Disseminate your results in renowned journals and at international conferences

• Master’s degree and PhD in quantum physics (or in a related domain)
• Background and strong interest in developing theoretical models and methods, as well as in implementing numerical optimization techniques
• Interest in working closely with experimental research teams
• Detailed knowledge of quantum physics and experience with quantum technology, ideally with color centers in diamond
• Strong analytic and numerical skills
• Ability to effectively communicate in written and spoken English
• Ability to work autonomously and in close interaction within a team
• Most importantly: enthusiasm to explore uncharted territory, develop, and follow your own ideas

• Master`s degree with PhD in physics, chemistry, materials science, chemical engineering, or related disciplines
• Fundamental knowledge in structural characterization of matter, ideally synchrotron methods (e.g. X-ray diffraction, X-ray spectroscopy, X-ray microscopy)
• Extensive experiences in the fields of catalysis, chemical hydrogen storage, energy sciences, interfaces
• Experience with programming languages (ideally Python)
• 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 idea

• Master`s degree with PhD in physics, chemistry, material science, chemical engineering, or related disciplines
• Extensive knowledge of X-ray diffraction, X-ray optics and X-ray instrumentation
• Experience in energy storage
• Experience with programming languages (ideally Python)
• 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

• Masters and subsequent Ph.D. degree in theoretical Physics/Electrical Engineering, Mathematics or a related subject
• Solid background and experience in machine learning and quantum computing
• Familiarity with Machine Learning and circuit QED is highly desirable
• Ability to work in a committed and independent manner with flexibility and open-mindedness for new challenges
• Interest in working in an interdisciplinary and international team of scientists
• Fluency in written and spoken English

We are looking for a highly motivated postdoctoral researcher who is excited in contributing to international research projects on topics at the interface between numerical linear algebra and application domains. For such an endeavor you have:

• Completed university studies (masters degree) and a doctoral degree in computer science, applied mathematics, computational science (physics, math, chemistry,..) and engineering or a related subject
• Very good knowledge of numerical linear algebra algorithms
• Extensive experience with parallel programming and high-performance computing, in particular with MPI, OpenMP and GPU programming models on large scales
• Strong programming skills, preferably in C++
• Some knowledge of Fortran, Python and Julia is an asset
• Some background knowledge in Machine and deep Learning is an asset
• A self-motivated personality, intellectual independence and the willingness of working towards the solution of challenging problems
• The ability of working on multi-disciplinary topics and in an environment which is team-oriented
• Very good command of written and spoken English

• University degree (Master) and doctorate in bioinformatics, computer science, data science or life science related fields with proven track record in data analysis/bioinformatics
• Knowledge in programming languages (e.g. Java, Rust, C/C++) and statistical analysis using R/BioConductor/python
• Experience with the analysis and integration (data fusion) of high throughput data such as NGS, metabolite profiling and/or plant phenotyping data
• Knowledge in the application of AI for data analysis and interpretation is advantageous
• Experience with plant omics data is a plus
• Experience with acquisition and administration of third-party funds is considered a plus
• Proven scientific communication skills in the form of scientific publications or equivalent
• Willingness to complement and collaborate with existing research units at the research center
• Excellent English language skills, both written and spoken are a requirement due to the international nature of the institute and collaborations

• PhD degree in quantum physics or a related field
• A background and strong interest in developing analytical models and numerical optimisation methods, and interest in working closely with experimentalists
• Detailed knowledge of quantum physics and experience with quantum technology
• Fluent command of written and spoken English
• Leadership and communication skills
• Ability to work autonomously in close interaction within a team
• And most importantly: enthusiasm to explore uncharted territory, develop and follow your own ideas

• Master`s degree in physics, chemistry, material science, chemical engineering or related disciplines
• Fundamental knowledge in structural characterization of matter, ideally synchrotron methods (e.g. X-ray diffraction, X-ray spectroscopy, X-ray microscopy)
• Experience in the field of energy materials
• Experience with programming languages (ideally Python)
• Fluent in written and spoken English
• Very independent and self-motivated way of working but also excellent teamwork skills
• Readiness for regular business trips
• High motivation to take on responsibility and develop own research ideas

• Master degree and subsequent PhD degree in Electrical-, Mechanical-, or Automotive Engineering, or Physics
• Strong knowledge of battery electrochemistry
• Experience in physics-based modeling and simulation in connection with electrochemical energy storage systems
• Familiarity and experience with programming languages, such as MATLAB or Python
• Independent and result-oriented way of working
• Strong ability to work in a team and with intern and extern partners
• Good communication skills in spoken and written English are mandatory, German skills are an advantage

• Completed Master`s degree and subsequent PhD degree in physics or related field
• Knowledge of lattice quantum field theory
• Strong background in C++
• Experience with accelerated and architectures, Linux and high-performance computing (HPC)
• Experience with profiling and performance optimization would be welcome assets
• Willingness present results at international conferences
• Good command of English, knowledge of German is not a prerequisite (language courses are offered)
• Structured and systematic working style and ability to work cooperatively in international teams

• Master’s degree in Physics, Applied Mathematics, Data Science, or Theoretical/Computational Chemistry and a subsequent PhD Degree
• Profound programming skills in python and its ML and NN modules
• Extensive background in ML, NN and related deep learning methods ideally with a focus on digital image processing
• Experience with experimental imaging techniques is preferable
• Experience in interdisciplinary projects and open-minded, flexible work ethics
• A motivated, tolerant attitude to supervise students responsibly; ideally some prior experience in supervision of students
• Fluent English skills both in speech and writing

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoc – Characterization of Plant Growth and Photosynthesis under Organic Photovoltaic Installations

Deadline :31.3.2024

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• Master Degree and PhD in plant sciences, plant biology, plant physiology, agriculture or other related disciplines
• Solid background in whole plant eco-physiology, plant growth and / or plant architecture
• Solid knowledge of methods to measure plant structure in the greenhouse and field
• Knowledge in using and interpreting 3D data from the PlantEye instrument is highly welcome
• Interest in working at the interface between applied and basic research
• Proven record of publications in a related field and the ability to summarize scientific results in project reports and journals
• Very good English communication and writing skills.