47 computer-"https:" "https:" "https:" "https:" PhD positions at Forschungszentrum Jülich
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required (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ) Our Offer: We work on the very latest issues that impact our society and are offering you the chance to actively
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environment within the Collaborative Research Centre TPChange program funded by the German Research Foundation and the European Research Infrastructure IAGOS Opportunities to attend conferences abroad and visit
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two companies. The project has partners from eight different EU countries. All 15 PhD projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications
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out within the DFG Priority Programme “DaMic - Data-driven Alloy and Microstructure Design of Sustainable Structural Metals” (SPP 2489), in close collaboration with a research partner responsible for
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strong interest in foundational machine learning research and its application to real-world scientific problems. You should bring: A completed university degree (Master or equivalent) in computer
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two companies. The project has partners from eight different EU countries. All 15 PhD projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications
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. Your Profile: A Masters degree with a strong academic background in physics, mathematics, computer science, computational neuroscience, or a related field Excellent quantitative and analytical skills
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opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs HEALTH & WELL-BEING: Your health is important to us. You can look forward to a comprehensive company health management
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for doctoral students (HITEC): https://www.hitec-graduate-school.de/home FAIR REMUNERATION: Remuneration is part of the EU funding program ‘Marie Sklodowska-Curie’ and depends on the personal requirements
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional