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/computational methods to model and interpret strong-field quantum-light-driven phenomena. Publishing results in peer-reviewed journals and presenting at scientific conferences Mentoring graduate and undergraduate
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
, prompt engineering, or retrieval-augmented generation (RAG) Experience deploying large-scale machine learning models in cloud environments. Create a Job Match for Similar Jobs About The University of North
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platforms that enable precise control over cargo loading, stability, release kinetics, and functional activity in tumor models. Responsibilities: Design, synthesize, and characterize polymeric nanoparticles
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., Datavyu), longitudinal data analysis (e.g., RI-CLPM, growth-curve analysis), multi-level modeling, and experimental study design. Expertise designing studies with parents, infants, and school-aged children
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the battery and propose design and operational strategies to overcome them. A core feature of your work will be combining multiphysics modelling for cell design with electrochemical testing, e.g. charge
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healthcare and foundational biological science. The primary focus will be on designing and implementing multimodal, agentic AI models for clinical support and creating novel deep learning models for genomics
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related to these general topics. Each focuses on gene regulation â“ and changes that occur in gene regulation â“ during stem cell development and differentiation. We use mice to model pediatric malignancies
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning
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physiology, data analysis and predictive modelling for the development of decision support tools. This position will also provide ample opportunity for the development of grant and scientific writing skills
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning