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Field
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*Strong publication record (relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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in ecological or social-ecological modeling (desired) Your tasks Contribute to the assessment of forest adaptive capacity Conduct statistical and spatial analyses to assess adaptive capacity
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managing human subjects research and handling sensitive data is preferred. • Strong quantitative skills, including proficiency in regression modeling, environmental mixtures analysis, and spatial methods
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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monitoring and profiling of breast tissue and systemic responses; Use of mouse models to study early tumour initiation; Application of single cell and spatial transcriptomics, lineage tracing, and multiomics
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have expertise in geometallurgy, applied geochemistry, and geo-environmental assessment, with advanced proficiency in integrating spatial data into 3D models using sophisticated interpolation techniques
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the spatial heterogeneity of CH4 emission using analytical footprint model and a lagrangian stochastic transport model. About the position Depending on the appointee’s competency and the type of employment
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model over the Contiguous United States, and evaluate model deficiencies and model improvements to improve the modeling of spatial heterogeneity of LST in land surface models. In Addition, Will Also
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implement an integrated, data-driven digital twin of the national energy system, capable of simulating and analyzing multi-energy infrastructures (electricity, heat, gas, hydrogen) across spatial and temporal