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Field
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generation. AI-based performance assessment in early design, integrating rapid analysis tools, multi-criteria performance estimation, and surrogate modeling. Human–AI collaboration in design, including agent
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latency constraints. - Federated and distributed learning for RAN hardware infrastructure management. o Knowledge of autonomous AI systems based on agents. Indicative skills/experience: - Multi-Agent
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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carry out the doctoral thesis for the 26/27 academic year. Adoptive cell therapyagainst cancer is a type of immunotherapy that is based on the use of agents that enhance the immune cells of the patients
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, systems, and hardware design. Experience in one or more of: LLMs, AI agents, embedded ML, physical modelling and simulation Strong programming skills in Python and C/C++, familiarity with ML deployment
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Application deadline: 5 January 2026 Apply now Do you want to develop predictive models that integrate omics and environmental data, advancing the field of precision prevention? Join the Institute for Risk
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at adapting our blood-brain barrier model to predict the brain permeability of extracellular vesicles and therapeutic agents. It by the use of cell culture, automation, high content imaging, TEER and
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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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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