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using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative opportunities with research groups in the MICRO-PATH consortium, spanning the Luxembourg Center
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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collaboration both within academia and with industry partners Expertise in one or more core areas of Generative AI, such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), diffusion models
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models Conducting microscopy experiments using conventional and super-resolution imaging techniques Conducting experiments using chemical biology-based protein engineering Maintaining accurate experimental
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design, development, and optimization of scalable AI inference pipelines Implement and experiment with LLMs, GNNs, multi-modal AI, and vision models Apply techniques such as quantization, pruning
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of Biochemistry, Molecular/Cell Biology, and/or BioEngineering Experience with fluidics devices, 3D printed devices, 3D cell culture models and bioinformatics/computational biology (e.g., R, Python) is an asset
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process thanks to the use of Deep-Reinforcement Learning (DRL) to orchestrate the joint use of multiple attack surface tools, Large-Language Models (LLMs) to refine their configurations and graph-based