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around three research axes: Axis 1: An investigation of legal and theological discourses on dispensation in the three religious traditions, and their possible interconnections, based on a corpus of
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learning and LLM frameworks like LangChain and agent-based LLM frameworks, Retrieval Augmented Generation (RAG). Experience with fine-tuning, deploying, and evaluating Large Language Models. Experience with
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., hydrogels, polymers, structured tissues), with applications in biomedical engineering, soft robotics, and more broadly in adaptive multiphysics systems. The developed models will be physically based and will
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they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S
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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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laboratories, including a shielded chamber for measurements of the effects of electromagnetic exposure and radiation. To strengthen our research in the field of artificial intelligence (AI)-based spectral
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. Description: Our group uses high resolution ground-based optical and near-infrared solar spectra to diagnose and model different manifestations of stellar activity. Nearby sun-like stars are a crucial sample of
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diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components
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Your Job: In an interdisciplinary team, you will implement approaches for the automated, large-scale availability and integration of energy system data and models, applying data science methods
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the Department of Biology at New York University is seeking a Postdoctoral Associate to study axonal mRNA transport and how this unique pathway influences mitochondrial quality control in neurons in the context