75 phd-image-processing "CNRS" Postdoctoral positions at Oak Ridge National Laboratory
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component (ELM) and its peatland-specific configuration (ELM-Peatlands), with a focus on improving the representation of nutrient cycling dynamics and their coupling to hydrological and ecosystem processes
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component (ELM) and its peatland-specific configuration (ELM-Peatlands), with a focus on improving the representation of nutrient cycling dynamics and their coupling to hydrological and ecosystem processes
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AI/ML surrogate models for inverse design of new materials and processes, incorporating simulated and experimental multi-modal datasets. Develop AI/ML approaches to bridge length- and time-scales in
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Requisition Id 17135 Overview: We are seeking a Postdoctoral Research Associate – Modeling, Controls, and AI for Thermal Systems to advance the design, operation, and maintenance of thermal systems
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advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak
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and perpetuation of values and ethics Basic Qualifications: A PhD in Microbiology, Bioengineering, Chemical Engineering, Molecular Biology, Genetics, or a related field completed within the last 5 years
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one
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architectural models, system-level simulators, and performance modeling frameworks for QHPC systems, capturing relevant characteristics of quantum processing units, classical HPC resources, interconnects, system
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and functionalized sorbents for the selective extraction and recovery of gallium (Ga), germanium (Ge), and other critical minerals from complex zinc-processing feedstocks. The successful candidate will