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Field
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will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using secondary data sources, such as national
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-fidelity modeling, digital twins, generative models, adaptive optimization, or autonomous experiment–simulation workflows. Excellent written and oral communication skills. Motivated self-starter with
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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international collaborators, you will simulate fragmentation processes and model the influence of surface potential on secondary ion yields in the OrbiSIMS instrument. Your insights will help us decode how
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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simulations, enhanced sampling, and kinetic modeling. Research activities will examine molecular interactions involving neurotransmitters and hormones, including norepinephrine and estrogen, and their effects
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 17 hours ago
involving environmental stress responses would also be beneficial. Skills in computational modeling, data science, or simulation-based research may support participation in activities that integrate genomic
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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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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning