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of the computational kernels of AI/ML models developed within the project, targeting their execution on embedded systems and heterogeneous computing platforms. The selected candidate will contribute
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characterization of packaging architectures for the System-in-Package (SiP) integration of GaN-based HEMTs: • Study and development of various packaging architectures (wirebonding and embedded chip) for high
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will assume the following tasks: • Macroscopic, inclusion, obtaining paraffin blocks and in OCT of tissues from experimental animal models and cell lines. • Microtomy of paraffin-embedded and frozen
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of microcontroller platforms or embedded systems, open-source software tools, and the development of software stacks and web interfaces for interacting with devices. Verifiable experience in the use and development
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embedded in an active implantable medical device and a portable external system to wirelessly power and communicate with it. Tasks to be performed: Scientific-technical activities and scientific-technical
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3D cardiac tissue by embedding synthetic circuits into hiPSCs. The applicant will receive training in a highly multidisciplinar field, acquiring expertise on circuit design, gene editing, hiPSC
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environmental datasets. Dissemination of results through scientific publications, conferences and stakeholder activities. The PhD candidate will be embedded in a highly international and interdisciplinary
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development of embedded intelligence and edge AI solutions within the cloud–fog–edge continuum. Participating in the creation of scalable and modular AI approaches for distributed environments. Supporting
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. Research Focus 7: AI-enabled Agricultural Materials (Qiang Li) Develop intelligent algorithms for agricultural materials genomics, including knowledge-embedded graph neural networks and inverse design
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de Lenguaje Natural Tareas: - Desarrollo de técnicas de fusión de LLMs con Embeddings de grafos de conocimiento para la recomendación de grafos en un caso de uso industrial - Diseño de experimentos con