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We invite applications for a NIH-funded postdoctoral researcher position in our computational lab at UMass Chan Medical School. We develop methods to reconstruct multi-modal, condition-dependent
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to do a proof of concept by first implementing the gravity anomaly using a boundary element method for homogeneous media (Cayol et al., 1997), before switching to a fictitious domain method for
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of the department's modern laboratory-, core- and animal facilities. The Department of Biomedicine focuses on innovation, entrepreneurship and collaboration with business and industry, and numerous researchers from
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, PETS has developed into a major research group, recruiting numerous new core, part-time, and adjunct faculty, and an experienced team of highly trained administrative and analytic staff. The current PETS
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, topological derivatives, among other methods, are expected to be useful for modeling the spectral characteristics of these shapes under evolving perturbations. In addition to its theoretical and intellectual
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the Research Group “ Numerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting September 1, 2025. The position is assigned to the research project "Randomization of Surrogates
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
have experience with algorithms, numerical techniques, and computational methods, specifically for uncertainty quantification, Bayesian statistics, and multivariate optimization; must have excellent
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
2025-2029, financed by national funds through FCT/MCTES (PIDDAC Workplan: Numerical study for the experimental detection of linear Breit-Wheeler (LBW) process by high-intensity laser-plasma interactions
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improving population genomic and bioinformatic methods to analyze palaeogenomic data, funded by research grants from Formas, Vetenskapsrådet and Riksbankens Jubileumsfond. The Human Evolution program has
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develop cutting-edge statistical models and computational methods to systematically extract knowledge of molecular interactions from single-cell multi-omic, multi-context data. As an integral part of our