26 high-performance-computing-"https:"-"CIPMM---Systemic-Neurophysiology" "https:" PhD positions at Forschungszentrum Jülich in Germany
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, i.e., high-fidelity virtual representations of agricultural ecosystems. These digital twins will enhance our understanding of ecosystem functioning, more specifically water and carbon fluxes, supporting
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) Expertise in further programming languages (in particular C++), GPU programming, parallel programming or high-performance computing are highly valued Keen interest in neuroscience is essential Experience with
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of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https
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to enable quantitative, high-resolution, time-lapse monitoring of soil properties and will be implemented using high-performance parallel computing. This PhD position offers the opportunity to work at the
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of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No Offer
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command of written and spoken English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), German is a plus Our Offer: We work on the very latest issues that impact our
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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in high-performance computing, numerical simulation Fluent in written and spoken English Independent, analytical, and team-oriented working style You are independent, motivated, and passionate about
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morphology with its performance (reactivity, selectivity, efficiency) and degradation under realistic long term deployment conditions Coordination and execution of in-house beam times Collaboration with other
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tunability and high-order dynamics to realize dendrite-inspired functional circuits. These circuits will subsequently be integrated as core computational modules within unconventional computing architectures