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around 2400€ net per month depending on background. Applicant Profile • PhD Degree in electronics, electrical engineering or computer sciences • Background in multiprocessor architecture, embedded systems
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or conferences. Open-source software developed by the team can be found at: https://github.com/GIN-iEEG Contact: Julien Bastin, PhD Inserm Research Director Head of the Brain, Behavior and Neuromodulation Team
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world-renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting-edge AI-ready/agentic infrastructure for data and model discovery, model
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(Python and R) to help build and refine the evidence synthesis engine, while leading quantitative analyses and evaluations of its performance. This is not a lead-developer role: software architecture and
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performance. The research focuses include: runtime-reconfigurable neural network software kernels for novel embedded systems architecture, performance models for adaptive AI workloads, on-device search and
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clusters with low power consumption and ultra-low and deterministic latency. The focus of the PhD activity is on demonstrating disruptive new network architectures for AI compute clusters utilizing optical
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 17 Sep 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Hours Per Week 37.5
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packaging, where EISLAB is responsible for the packaging part within a European consortium. Subject description Cyber-Physical Systems focuses on integrated software and application architectures with
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the opportunity to work in a world-renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting-edge AI-ready/agentic infrastructure and data systems
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responsible for the packaging part within a European consortium. Subject description Cyber-Physical Systems focuses on integrated software and application architectures with implementations of massively