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validate a comprehensive genetic panel for the molecular diagnosis of pituitary diseases. Using next-generation sequencing (NGS) technologies and a bioinformatics algorithm, the panel will identify genetic
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validate a comprehensive genetic panel for the molecular diagnosis of pituitary diseases. Using next-generation sequencing (NGS) technologies and a bioinformatics algorithm, the panel will identify genetic
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Computational Biology group leads the computational biology efforts to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done
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under the following conditions: OBJECTIVES | FUNCTIONS Analyze mass spectrometry data for microbial identification. Assist in the curation of spectra and the development of identification algorithms
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knowledge of adaptive optics systems, including wavefront sensors, deformable mirrors, and real-time wavefront correction algorithms. Familiarity with optical systems, particularly in high-resolution contexts
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configurations and DNSSEC security validations. Implement the Kea DHCP service (or an equivalent solution) with a database backend. Develop APIs for migrating static data and test HA and failover algorithms
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of the call Past experience in AI algorithms Past experience in Research Projects EVALUATION CRITERIA The selection will be based on the following criteria: Academic record (50%) Past Experience in AI
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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hospitals. PRIMARY DUTIES AND RESPONSIBILITIES: The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration
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from users and participating academies. They will be responsible for evaluating the performance of personalized training plan recommendation algorithms, predictive models of user evolution, and class