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Field
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with the nation-wide research priority area “LaSTing : Robust Assessment & Safe Applicability of Language Modeling: Foundations for a New Field of Language Science & Technology,” which is funded by
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gene expression programs, and how perturbations in these regulatory layers drive pathological states, particularly in aggressive cancers. Conceptual knowledge in these areas will be highly relevant
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encouraged. BSL-2 pathogens will be utilized. The successful applicant will be able to synthesize experimental data into conceptual models. The Kaelber lab is located in the Institute for Quantitative
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capabilities. Key Responsibilities: Capturing requirements and analyzing specifications for future detector systems Performing conceptual design and system-level optimization using emerging computing
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of conceptual and numerical models describing sediment material properties, sediment and water transport, leveraging in-situ and indirect measurements such as geophysical and/or remote sensing
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studying the relationship between democracy and demagogia in the history of political thought. The work will focus on analyzing how demagogia has been conceptualized as an internal possibility within
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collections that can serve as references for future studies, (ii) enhancing the understanding of physical mechanisms and causal pathways to strengthen attribution analyses and model development, build
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mechanistic modelling, the project seeks to advance fundamental understanding of how complex environmental perturbations influence infectious disease emergence, spread, and persistence across coupled human
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for the conceptual framework, design, and implementation of these machine learning models, ensuring trustworthy computations and scalability on the DOE’s leadership computing facilities. The focus will be
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning