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massively parallel selection experiments to tackle the fundamental encoding problems of molecular biology. Towards this goal we have developed, benchmarked, and applied at scale experimental methods that use
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visualization of scientific data. In carrying out the estimation of statistical uncertainties and identification, control and correction of systematic biases in Quantum Monte Carlo methods. In the optimization
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at the Biochemistry and Molecular Biomedicine Department in the Faculty of Biology of the University of Barcelona. The Principal Investigator of the group is professor Vicent Casadó Burillo. Where to apply Website http
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methods for uncertain data, including variational autoencoders for the generation of coherent surrogate datasets with incomplete or imprecise information. Implementation of similarity-based learning and one
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methods to automate the mechanical design process and structural validation of beams used in the ship's equipment. • Develop methods for optimizing the design of beams. • Integrate the developed methods
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population register data and apply advanced causal inference and longitudinal methods, including marginal structural models, inverse probability weighting, and other approaches that address time-varying
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in which the successful applicant will collaborate: 1.1. Name of the project: “Water cycle characterisation and GeoSAR data estimation methods”. 1.2. Reference: PID2024-161188OB-C22. 1.3. Funding
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Pastrana, Guillermo Suarez-Tangil. IoC Stalker: Early Detection of Indicators of Compromise. Annual Computer Security Applications Conference (ACSAC). December 9–13, 2024. (link: https://suarez
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: Collection, analysis and interpretation of experimental data, using statistical software and other methods to guarantee the accuracy of the results. Dissemination and publication: Assistance to congresses
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super-resolution microscopy with genomic approaches. AI-driven and computational methods are applied to analyze super-resolution imaging data to elucidate, identify, and reconstruct the biological