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. Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. In CoRR, abs/2311.16452, 2023. [33] S. Lamsiyah, A. El Mahdaouy. A Reinforcement Learning-based Method
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of Distributed Mixture-of-Experts (MoE) and Small Language Models (SLMs) to create autonomous, intent-driven networks. This isn't just about connectivity; it’s about building a collaborative, agentic ecosystem
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., 2022. Calibrated Photoacoustic Spectrometer Based on a Conventional Imaging System for In Vitro Characterization of Contrast Agents. Sensors 22, 6543. https://doi.org/10.3390/s22176543 Nicolas-Boluda, A
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fungal infections. Emerging research is exploring radiometals conjugated with targeting molecules for in vivo imaging of infections via PET or SPECT. These agents can also be linked to therapeutics
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks
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cues play a role analogous to conditioned stimuli: they are signals that, once learned, allow the agent to anticipate the consequences of its actions. Scientific Motivation: Learning-based navigation
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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market using data available on online recruiting platforms, deploying state-of-the-art approaches in Natural Language Processing, Semantic Web, and Agent-based Modeling. For this purpose, an extensive