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, including meta-analysis using PLINK 1.9 (fixed-effects inverse-variance model), conditional analysis using REGENIE, and fine-mapping of HLA–protein associations. You must hold a first degree in Genomic
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partners to coordinate data sharing and meta analysis efforts ML – Develop and validate cancer risk models Manuscripts and grants – Contribute to scientific publications, presentations, and grant
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. Context Modern computing systems ranging from high-performance computing (HPC) to embedded AI and automotive platforms face increasingly complex and interdependent design challenges. These systems must meet
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including: high-throughput (HTC) and high-performance (HPC) computing; research data management (RDM), storage and archiving; edge computing; and highly-secure platforms for hosting/processing sensitive data
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Development Division of the Information Technology Services Directorate. Our AI/ML models are heavily centered on Microsoft Azure and related AI cloud technologies with High Performance Computing (HPC
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research, or a related field is a must • Proficiency in bioinformatics or clear motivation and prior exposure; HPC and metagenomics pipeline experience preferred • Experience with next-generation sequencing
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. Perform large-scale quality control (QC), phasing and imputation of genotypic data, population structure testing, association studies, meta-analysis and fine mapping Contribute to building, benchmarking