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-tasks and language models. This position is part of SDU’s initiative to develop energy-efficient AI accelerators based on alternative model architectures that cannot be leveraged as efficiently
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predictive or generative methods for materials discovery. Work with state-of-the-art neural network architectures applied to materials data. Publish scientific papers and present research results in top
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
the European Green Deal, Sendai Framework, and UN Sustainable Development Goals. DCs will benefit from an immersive training structure comprising cross-sectoral secondments, workshops, and summer schools
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
, REUNATECH supports the European Green Deal, Sendai Framework, and UN Sustainable Development Goals. DCs will benefit from an immersive training structure comprising cross-sectoral secondments, workshops, and
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resilience-centered approach, REUNATECH supports the European Green Deal, Sendai Frame-work, and UN Sustainable Development Goals. DCs will benefit from an immersive training structure comprising cross
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre
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, suitable for wearable or implantable devices. The research will focus on hardware-software co-design, from modeling spiking behavior to implementing scalable architectures on silicon. Key research themes