2,112 embedded-system "https:" "https:" "https:" "https:" "IFM" "IFM" "IFM" positions in Germany
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tools, VLSI, SoC, RISC-V, compilers approximate computing, memory-centric computing, and embedded systems, (specific topics:) experience with assembly, RISC and other Instruction Set Architectures
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6 Mar 2026 Job Information Organisation/Company Cluster of Excellence ROOTS Research Field History » Archaeology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application
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socio-economic impact. TransforM is deeply embedded in Munich's vibrant innovation ecosystem. Anchored by two of Germany's leading research universities – Technical University of Munich (TUM) and Ludwig
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
Germany's largest scientific organisation. Where to apply E-mail personal@hzdr.de Website https://www.hzdr.de/job2186e Requirements Additional Information Website for additional job details https
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available in the further tabs (e.g. “Application requirements”). Programme Description SECAI scholarships were created to support outstanding students who intend to study AI or a related field at TU Dresden
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focused with about 1000× concentration onto a solar cell with a size of only about 600 µm × 600 µm, i.e., very small areas. The work is embedded in the WSS project (https://www.ise.fraunhofer.de/de/presse
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is thus required, experience in clinical or biopsychological research is of benefit. Your profile: - Approbation as a psychological psychotherapist in the field of children and adolescents
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embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments
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22.01.2026, Academic staff This PhD position focuses on developing resilient ISAC architectures. This project aims to implement, test, and demonstrate resilience strategies that enhance ISAC system
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., regression, classification) and neural networks (e.g., CNNs, RNNs) Preparation of ML models for inference on edge systems (edge AI, embedded AI) Collaboration on MLOps/DevOps processes (e.g., versioning