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are being investigated for energy-efficient artificial intelligence (AI) applications. Some examples are RRAM or STT-MRAM collectively known as memristor-based Computation-in-Memory (CIM) accelerators
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looking for a highly motivated PostDoc candidate who wants to work on efficient and reliable digital CIM-based AI accelerator design for future neuromorphic accelerators. The candidate will work on the
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collectively known as memristor-based Computation-in-Memory (CIM) accelerators. However, these new technologies and computing paradigms face various design challenges in terms of design and technology challenges
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accelerator design for future neuromorphic accelerators. The candidate will work on the following: Designing efficient digital CIM architecture using advanced CMOS nodes Develop system architecture for digital
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, which causes reduced performance and accelerated material degradation in seawater. This project will experimentally investigate cavitation erosion in composite materials and develop a structural health
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global CO₂ emissions, largely due to its dependence on clinker—the key constituent of conventional cement. To accelerate the decarbonization of construction materials, the C-Sink Project (funded under
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Job description The cement industry is a major contributor to global CO₂ emissions, largely due to its dependence on clinker—the key constituent of conventional cement. To accelerate
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the heating of microscopic aggregates of thermoplastic cut tapes, with the goal of accelerating process development for circular materials. You will generate valuable multi-scale data (micro- to mesoscopic
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department’s research activities aim at accelerating the energy transition towards sustainable energy. Job requirements We are acutely aware that we are a diverse society and not every talented applicant will
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technology from solar cells to PV systems with their power electronics and storage options. The ESE department’s research activities aim at accelerating the energy transition towards sustainable energy. Job