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Job Announcement ref. #02-26004 Senckenberg – Leibniz Institution for Biodiversity and Earth System Research (SGN), headquartered in Frankfurt am Main, is seeking to fill the following position
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methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision-making in IoT, wireless communication, and remote sensing systems Collaborate with multidisciplinary
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onboard software modules. To assist project PI to coach research students Job Requirements: A bachelor’s degree in relevant fields with past experience in embedded system, wireless network and software
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California State University, Long Beach | Long Beach, California | United States | about 19 hours ago
Engineering or a closely related field. Areas of expertise may include, but not limited to, cybersecurity, computer and network security, hardware and embedded system security, cryptography, privacy-preserving
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computational imaging, applied mathematics, and structural biology. The research environment is embedded in Linköping University and closely connected to SciLifeLab and the national DDLS program. Read more about
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an ideal environment for combining cultural and family activities with an active lifestyle. Where to apply Website https://jobs.50skills.com/ru/is Requirements Research FieldEnvironmental scienceEducation
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to drive recruitment outcomes. Contribute to on and off‑campus recruitment events and outreach activities Mahi & Wāhi / Utu | Work pattern, location & salary This is a permanent role working 37.5 hours per
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of Geneva and Leiden University. The postdoctoral position will be embedded within the Lorentz Institute for Theoretical Physics (https://www.lorentz.leidenuniv.nl/ ). The application process The application
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embedded systems to emerging unconventional platforms (e.g. probabilistic computing). The research will define the architectural requirements for the next generation of robotic hardware. Prospective
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having