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the cellular and molecular pathways disrupted in brain disorders such as schizophrenia and autism, by utilizing recent advances in genetics and genomics. We are developing and applying tools to understand how
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and porting of scalable science applications and algorithms for OLCF and other leadership computers. Debugging and tuning applications for high performance. Developing performance models of existing
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A postdoctoral research associate is sought to develop an experimental (hardware) platform that enables efficient exploration of complex parameter spaces. The platform will integrate comprehensive
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mechanics, machine learning or applied/computational mathematics. ● Demonstrated ability to carry out original mathematical derivations and/or develop computational tools, evidenced by publications
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faculty position at the rank of Assistant Professor in Quantum Information Theory, with an anticipated start date of August 1, 2027. We seek candidates capable of developing an innovative research program
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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remains largely unexplored and represents a fascinating frontier for molecular computing. The development of new methods will be necessary to enable the manipulation of data within complex molecular
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Research Infrastructure? No Offer Description Mission: Develop an end-to-end (E2E) Digital Twin framework for the optimization of satellite constellations dedicated to disaster monitoring (forest fires and
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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and development of robot localization algorithms and computational methods. Responsibilities: Research and development of robot localization algorithms and computational methods Responsible for setting