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flexible alternative. Thanks to their significant thermal inertia and ultra-low-temperature operation, DHCNs can absorb surplus renewable energy, respond to market signals, alleviate grid stress, and provide
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interdisciplinary project to contribute to developing a community-based, digitally empowered approach to retrofit program design to empower marginalized communities. The project includes direct hands-on work with
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Degree Doctorate Course location Potsdam In cooperation with The innovative PhD and postdoctoral scholarship programme is offered in conjunction with the Faculty of Digital Engineering, a faculty
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, digitally empowered approach to retrofit program design to empower marginalized communities. The project includes direct hands-on work with households, neighborhood associations, local government
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specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling
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of sound waves, as well as transducers and related signal processing, in a wide range of scenarios: sound for the communication between humans (speech and music); the influence of sound (noise) on humans and
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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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should have strong digital signal processing and mathematical backgrounds evidenced by grades and/or prior publications. Additionally, the candidate should have expertise or strong interest (evidenced by
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that support spike-based processing and memory-efficient computation using SSMs, targeting edge-AI scenarios in wearables, robotics, or sensor networks. Research area and project description The project will co
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to dimension the reserves for balancing these power systems with manual and automatic reserves such as mFRR, aFRR and FCR. This PhD project will model different balancing principles including MARI and PICASSO