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Postdoctoral Associate – National Tutoring Observatory Postdoctoral Associate – National Tutoring Observatory Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers
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) Experience with Large Language Models solutions (agents, RAG) Additional Information PERSON SPECIFICATION We want to employ people with a wide variety of experiences. We welcome applications from all sections
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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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ambulatory health care settings. Assessing developmental, psychosocial, emotional and cultural needs using a strengths-based approach, the child life specialist provides developmentally appropriate education
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• Familiarity with LLM in-context learning and prompt engineering • Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented generation, tools/chains, and LLM agents
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other media; and 4) to train and direct support personnel. The candidates are expected to have experience in animal bone marrow transplant models, DNA repair pathway, flow cytometry, and lentiviral-based
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. The ideal candidate is passionate about graduate education, committed to evidence-based practice, and eager to support students’ professional development within a collaborative academic community. The
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architectures. This includes among other: (a) design and implementation of machine learning and GenAI models, (b) efficient training and inference on GPU-based systems, (c) fine-tuning and optimization of large
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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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Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences | Poland | about 1 month ago
properties and a variety of potential applications. Application of the molecular dynamics methods combined with the approach based on the thermodynamic models of multicharged surfactant adsorption can provide