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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-SEA-2025-0182 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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/business network formation in low-income countries (possibly, in conflict affected areas, CAF). We seek a candidate with expertise in both empirical and theoretical economics and strong coding skills
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scientific programming, preferably Python or C/C++ • Strong written and oral communication skills Desired Qualifications: • Familiar with mathematical and coding aspects of neural networks • Contributions
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, and analysis by using concepts and methods from machine learning, including pattern recognition, graphs, and complex networks. ** Specific Research Areas: * Develop concepts and algorithms to analyze
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have: experience with spiking neural networks and neuromorphic architectures; deep knowledge about our brain and how it makes decisions; coding reinforcement learning algorithms/feedback systems and
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approaches, high-throughput methodologies. Excellent communication skills. Interest in mathematical modeling of metabolic and regulatory/signaling network. You will have access to state-of-the-art research
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multidisciplinary and highly diverse environment. Active in networks for acquiring research funding, and have ambition and experience in working closely with companies and government agencies. Good communication
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teaching within the Science Faculty. The KdV Institute participates in the NWO research clusters GQT, STAR, NDNS+ and DIAMANT and in the Gravity programme NETWORKS. There is formal (and informal) cooperation
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Technologies AMU, Uniwersytetu Poznańskiego 10, 61-614 Poznań, Poland Monthly salary: 8987 PLN (gross amount, which includes social security contributions, the tax, and the net amount; it is the amount specified
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
Job Code: 07/2025 Job Offer from November 21, 2025 We are seeking to fill one postdoctoral position as part of the Simons Collaboration on Learning the Universe . In this international network