37 coding-"https:" "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich in Germany
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development, version control systems, Linux environments, and SSH. Very good command of written and spoken English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options: https://go.fzj.de/womens-job-journey Eligibility rules
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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Website https://www.fz-juelich.de Street Wilhelm-Johnen-Straße Postal Code 52428 E-Mail info@fz-juelich.de Phone +49 2461 61-0 Fax +49 2461 61-8100 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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/InstituteForschungszentrum JülichCountryGermanyCityJülichGeofield Contact City Jülich Website https://www.fz-juelich.de Street Wilhelm-Johnen-Straße Postal Code 52428 E-Mail info@fz-juelich.de Phone +49 2461 61-0 Fax +49 2461
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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of offers available1Company/InstituteForschungszentrum JülichCountryGermanyCityJülichGeofield Contact City Jülich Website https://www.fz-juelich.de Street Wilhelm-Johnen-Straße Postal Code 52428 E-Mail info
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JülichCountryGermanyCityJülichGeofield Contact City Jülich Website https://www.fz-juelich.de Street Wilhelm-Johnen-Straße Postal Code 52428 E-Mail info@fz-juelich.de Phone +49 2461 61-0 Fax +49 2461 61-8100 STATUS: EXPIRED X (formerly
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learning, physics-informed neural networks, graph neural networks, transformers, convolutional defiltering methods, etc.) for the integration in multi-physics simulation codes You will develop code for and
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genomic approaches Application of the modeling approaches in relevant downstream tasks Co-development of high-performance computing AI training codes for the first European Exascale Supercomputer JUPITER