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by information and communication technology which could lead 20% of global energy production to be consumed by the adoption of artificial intelligence. Therefore, “unconventional” computing
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MSCA Doctoral Network HINA - Hybrid INtegration of Alkaline niobate - tantalate films for advanced photonic and piezoelectric devices | Montpellier, Languedoc Roussillon | France | 5 days ago
20 Sep 2026 Job Information Organisation/Company MSCA Doctoral Network HINA - Hybrid INtegration of Alkaline niobate - tantalate films for advanced photonic and piezoelectric devices Research Field
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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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4 Sep 2026 Job Information Organisation/Company INSA Strasbourg Research Field Engineering » Electrical engineering Engineering » Computer engineering Researcher Profile Recognised Researcher (R2
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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to an aluminium drum resonator, referred to as a double-drum resonator [1]. The team has recently achieved in implementing reservoir-computing in the coupled drum resonators and successfully fabricated networks
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5 Sep 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Engineering Computer science Mathematics Researcher
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with 3D cell culture, organoids or tissue engineering will be considered a strong advantage. Experience with image analysis software (ImageJ/Fiji) and scientific computing tools (Python, R or equivalent
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18 Sep 2026 Job Information Organisation/Company AMPÈRE INSA-LYON Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1
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UniGEM). Within UniGEM, this internship aims to engineer the features input into the neural network and to compute their values using real malaria parasite data. These values will be used in a subsequent