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are seeking a highly motivated PhD candidate to develop efficient on-device generative AI systems based on large language models (LLMs). The project focuses on creating compact, low-latency, and energy
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for modelling infection including macrophages, organoids, zebrafish, primary and clinical samples. Embedding within the Institutes of Biology and Chemistry at Leiden will enable the candidate to maximize
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DFT modelling, are a plus. Project description and responsibilities The position entails the synthesis of new ruthenium-based photocages. You will be integrated in the MCBIM group (https
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PhD candidate in Design and synthesis of pyrophosphate mimetics to study enzymes involved in natural
Universities). Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3 %), training and career development. Our individual choices model gives you some
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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) Establish LCI models for the port call process Evaluate existing marine impact categories, and develop novel cause-effect pathways for marine impacts Establish probabilistic inventories for prospective LCA
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36-hour week. Lots of options when it comes to secondary employment conditions; we can, for example, discuss options for a sabbatical or paid parental leave. Within our terms of employment individual
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and have access to state-of-the-art industry experts, data and knowledge, allowing you to make an impact during your PhD research. In this position you will work with real world data and models, aimed