At the Institute for a Sustainable Hydrogen Economy (Institute for a Sustainable Hydrogen Economy – Catalytic Interfaces for Chemical Hydrogen Storage (INW-1), Director Hans-Georg Steinrück), we investigate mechanisms and processes of chemical hydrogen storage using advanced methods (including large-scale research facilities) as well as modern data reduction and data evaluation methods. The current project deals with the use of machine learning / artificial intelligence and big data science in the field of synchrotron research.

• University degree (Master) and doctorate in bioinformatics, computer science, data science, biophysics, or life science-related fields with a proven track record in bioinformatics, biophysics, data analysis, and simulation sciences
• Very good practical experience in molecular biology, Next Generation Sequencing, and structural biology
• Extensive experience in analyzing large datasets (especially genomics, transcriptomics, metagenomics, enzyme data, and structural data)
• Experience with the application of machine learning methods for data analysis and interpretation
• Knowledge in programming languages (e.g. Java, Rust, C/C++, Python) and statistical analysis using R/BioConductor/python
• 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

If you are interested in emerging technologies, this might be the perfect opportunity for you! We are looking for someone who can come up with unique circuitries, applications, or algorithms to integrate neuromorphic-inspired computing paradigms. Your main tasks will include:

• Identify areas where neuromorphic-inspired paradigms can be applied
• Develop concepts to integrate CMOS circuits with neuromorphic elements by custom analog, digital, or mixed-signal circuits
• Publish your findings in scientific journals and present your results at international conferences
• Supervise doctoral researchers and students
• Explore new funding opportunities

• Master`s and PhD degree in physics, chemistry, biophysics or related disciplines
• Strong background in statistical physics and in (quantum or atomistic or coarse-grained) simulations of biological systems
• Previous experience with normal mode analysis is appreciated
• Records proving the accomplishment of a successful independent work
• Good knowledge of written and oral English
• Good communication skills

• 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

• 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

As a Postdoctoral Researcher in MRI / PET / Computer Science you will lead our newly established SMART|Lab Biomedical Imaging in Kutaisi, Georgia. The facility has been developed as part of the German Georgian Science Bridge (GGSGB-PLUS), which aims to foster scientific collaboration and exchange between Germany and Georgia, and will be run as a joint collaboration between the Forschungszentrum Jülich (INM-4/IAS-8) and Kutaisi International University. It is anticipated that the Lab will play a pivotal role in advancing the clinical diagnosis and therapy of oncological diseases through the use of machine learning in conjunction with cutting-edge imaging techniques involving MRI and PET. 

• Master and PhD in physics or a related field
• In-depth experience with quantum control experiments on quantum dot qubits
• Good software development skills
• Experience with sub-Kelvin cryogenic techniques
• Strong aptitude for mentoring students
• Good communication skills
• A strong drive to conduct ambitious, cutting edge research towards scalable quantum computing
• A research track record commensurate with our ambition

• A completed scientific university degree (Master`s degree) in the field of bioinformatics, computer science, mathematics, engineering, natural sciences or economics, or a related degree programme, followed by a completed doctorate/Phd studies
• Experience in big data analyses in connection with cloud technologies and workflows
• Good knowledge of sequence analysis and metagenomics, especially in the processing of Illumina and ONT data
• Very good programming skills (e.g. in Python or comparable) and knowledge of relevant technologies (e.g. Git, Docker, Nextflow)
• Very confident with Linux/Unix
• Fluent written and spoken English
• High degree of independence and willingness to familiarise yourself with complex topics
• Very reliable and conscientious working style
• Good publication performance
• Willingness to actively impart knowledge, e.g. by supporting the planning and implementation of training courses
• Willingness to travel and participate in conferences, networking events and project meetings

We are looking for a candidate to bring different qualities to the position:

Essential:

• A PhD in chemistry/physics or related area
• Experience with NMR, MRI, or hyperpolarization technologies
• Experience in working within multidisciplinary and collaborative research environments
• Proven high-level problem-solving skills
• Demonstrated capacity to work productively within a team
• A track record of scientific publishing and presentation of scientific results at conferences
• English language proficiency

• Scientific university degree (Master`s/Diploma) related to the life or natural sciences or related fields, preferably with a doctorate/Phd studies
• Practical experience in data-driven science (e.g. data analysis, applied statistics, visualisation, etc.)
• Strong interest, experience and/or formal qualifications (e.g. Carpentries, RStudio instructor certification, etc.) in teaching computer-based research skills in targeted training courses
• Working knowledge of programming/scripting languages such as Python, R, Bash and concepts of scientific data processing such as version control, cloud computing, cluster computing, workflow management, data literacy, etc.
• Very confident with Linux/Unix
• Knowledge of sequence analysis and metagenomics, especially in the processing of NGS data is an advantage
• Strong interpersonal skills and ability to work effectively in a team
• Strong communication skills, verbal and written expression in German and English
• Enjoy working in an interdisciplinary, science-orientated environment at the interface between science, teaching, administration, politics and business
• Willingness to travel and actively participate in conferences, networking events and project meetings

• 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