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Field
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atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible computational workflows, collaborate with
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—integrating first-principles simulations with machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive
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-transcriptional gene regulation; kidney biology or polycystic kidney disease; mouse genetics, transgenic mouse models, and animal phenotyping; mammalian cell culture, primary cells, or kidney organoids; or RNA
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-based simulations in VR/AR to facilitate the acquisition of complex physical tasks. This includes real-time feedback loops, biomechanical modeling, and adaptive training environments. Social & Soft Skill
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simulations to analyse underwater vehicle performance Access to world-class facilities at DSTG Fishermans Bend and the Australian Maritime College Full time and Fixed-Term (June 2028) based in Victoria with
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 4 hours ago
Materials. The learning objectives for this project are: (1) use atomistic simulation software and AI/ML techniques on sensing materials database development, (2) analyze the modeling results, and (3) learn
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theoretical aspects of wave propagation and complex systems. Experience with optical experiments, numerical simulations, or computational modeling. Programming and simulation skills in MATLAB, Python, COMSOL
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the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power electronic conversion, energy and hydrogen storage, downstream processes
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. Work will include designing and implementing mixed-method studies with human participants; collecting person-level sensor/simulator and field data; analyzing repeated-measures and multimodal behavioral
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generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption