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Number: 16451 School: Harvard Medical School Position Description: We are seeking a highly motivated post-doc trainee to join Dr. Norbert Perrimon's group in the Program of Genetics at Harvard Medical
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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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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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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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disease challenges and drivers of antibiotic use in swine production. The goal is to identify genetic and regulatory factors that influence disease outcomes in S. suis and G. parasuis. These insights
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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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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