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, which are based on the resonating behavior of their meta-atoms and which suffer dissipation losses, the envisioned research will be based on the mutual and external synchronization of tunable self
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. Metagenomics, meta-transcriptomics and metabolomics data analysis and extensive familiarity with gut microbiome research. Machine learning for genomics (representation learning, generative models, causal
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into embedded prototypes to demonstrate real-world feasibility. The overarching goal is to bridge high-level algorithmic innovation with energy-aware hardware deployment, enabling intelligent sensor systems
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networks, online analysis with delay, and theory of distributed algorithms. Job description In our group, we try to apply and unite the approaches and techniques of theory and practice. Some members of our
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to detect input and user intent. The purpose of this is to support emerging AR platforms (such as Meta Orion's EMG neural wristband ). We will explore how sensed differential signals can be leveraged
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develop cutting-edge algorithms and AI-based solutions for data processing and validation and provide scientific expertise for the implementation of future remote sensing missions. The team’s work bridges
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: Lightweight, real-time models using quantization, compression, and adaptive execution. Hardware–algorithm co-design: Cross-layer optimization aligning ML algorithms with embedded hardware. Distributed and
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processing and analysis. The LISA ground segment is a distributed facility (the LISA Distributed Data Processing Center), for which LISA member states contribute national centers with specific commitments and
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experience. Strong programming skills in Python and experience with modern ML stacks (PyTorch, HuggingFace, distributed training). Experience in LLMs, vision–language models, multimodal learning, or clinical
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earth observation technologies. Our researchers develop cutting-edge algorithms and AI-based solutions for data processing and validation and provide scientific expertise for the implementation of future