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-efficient accelerator architectures by designing digital and mixed-signal blocks for SSM inference in edge-AI systems. The successful candidate will explore novel SSM architectures that support sequence
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-design SSM-inspired spiking neural network (SNN) cores and integrate them with a low-power RISC-V processor. The PhD candidate will develop spike-based computing blocks and explore hybrid analog/digital
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test digital prototypes with stakeholders Apply metagenomic sequencing to validate microbial contamination trends Analyze microbiome and operational data to identify risk factors Contribute to teaching
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, the project implements an approach combining social, institutional, and digital history across three work packages: (i) Communities, (ii) Hierarchies, and (iii) Infrastructures. To operationalize its approach
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where variable renewable energy sources are involved. Emerging digital and cyber-physical systems technologies are an integral component of grid interactive efficient buildings. Through advanced control
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PostDoc in the project). Collaborating with fellow researchers across the UPLIFT network, including those focused on digital twins at DTU Chemical Engineering- As a PhD candidate, your work will adapt
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than RGB will be actively researched. Exploring 3D canopy modelling and plant growth dynamics for digital twin integration. Self-supervised learning will generate multi-modal agricultural pre-trained AI
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, you will join the Power-to-X and Storage (PtX) section within the Power and Energy Systems (PES) division. The PtX section combines multidisciplinary research in energy storage and flexibility, digital
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Digital Twins for Wind-Offshore and GREAT: GRid Enhancement for Ancillaries in Tomorrow’s power systems, where you will interact with researchers and experts from TotalEnergies and many other research
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described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed