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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 months ago
, seasonal and solar cycle dependent variabilities. These different phenomena make characterization of regional ionospheric dynamics a complex problem. New observational capabilities and sophisticated data
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, computer science, biomedical engineering, or a closely related area. You will have experience in one or more of the following: (non-autonomous) dynamical systems, complex networks, bifurcation theory
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regeneration from birth through senescence. By joining our team, you will dive into the complex mechanisms of stem cell fate, investigating how the immune system’s delicate homeostasis contributes to organismal
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at international conferences. Your profile PhD (degree or almost completed) in Physics, Applied Mathematics, Complex System or a related field. Strong background in mathematical modeling, machine learning
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the Department of Internal Medicine; plans, designs and executes experiments of considerable scope and complexity in the assigned research lab focusing on Lung fibrosis, senescence, and wound repair; collects and
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behavior and identify therapeutic leverage points Develop and characterize complex 3D patient- and iPSC-derived models Design, perform and interpret complex experiments; ensure high data quality and
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which complex interactions involving rock, soil, water, air, and living organisms regulate the natural habitat and determine availability of life-sustaining resources”. Its limits range from the top of
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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Discovery Innovation Network foundation, NNF grant number: NNF23SA0088590. The position focuses on experimental development at the interface of microfluidic organ-on-chip systems and metabolic magnetic
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the theoretical foundations of machine learning itself, leveraging tools from quantum information, statistical mechanics, and complexity theory to understand and enhance modern AI. Successful candidates will work