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related to staff position within a Research Infrastructure? No Offer Description Support in research on Bayesian optimization methods. Data analysis and modeling. Development of prototypes and software
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signatures of logical representations and inferences induced by the passive inspection of simple scenes. Building upon previous results, we propose to realize four goals: Understand the nature
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of parametrization of these models based on least squares and Bayesian calibration techniques employing longitudinal series of anonymized PSA data from patients. 3) Analysis of the predictions, parameters, and
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other territorial units. •Development and application of causal inference techniques (difference-in-differences, propensity score matching, multilevel models) to estimate the electoral effects of urban
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publications in international academic journals. • Experience in the use of causal inference methodologies applied to spatial data. • Knowledge and advanced use of quantitative techniques (regressions
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. Furthermore, he/she will participate in the development of computer vision algorithms for hyperspectral image analysis and mathematical models for knowledge inference, with the aim of estimating the key
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analyze and interpret multi-omic data to identify spatial patterns, cellular neighborhoods, and gene programs associated with drug resistance. Develop predictive models to infer tumor evolution and
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-performance training/inference systems, your contributions will be critical to our mission. We are hiring for multiple specializations within this role, and we encourage candidates with a deep passion for any
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focuses on understanding how the evolution and persistence of cancer cell populations are influenced by the influx of mutations and by selective pressures, as inferred from mutation data. To address