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Field
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been oriented around high performance computing (HPC) but are increasingly migrating to cloud-based solutions. We are seeking a talented software engineer to bring in this transition. You'll Be Solving
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, computer science, physics, statistics, mathematics or related field. Demonstrated developing and implementing federated learning methods (such as optimization & aggregation, privacy techniques and personalisation
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scalable cloud platforms to streamline data processing, analysis, and sharing. The successful candidate will have a strong foundation in software engineering, data engineering, and cloud computing, with a
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/ML frameworks (e.g., TensorFlow, PyTorch, FLOWER). Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and on-premise cloud platform such as VMWARE, and heterogeneous infrastructure
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data analysis Understanding of cloud computing environments (AWS and/or Google Cloud) Application Instructions Interested candidates should submit the following materials through Interfolio: Cover letter
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Python, Java, or C++, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, FLOWER). Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and on-premise cloud platform such as
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and/or MD in computational biology, bioinformatics, genomics, or other related fields. Proficiency with high-throughput sequencing data analysis and cluster/cloud computing. Expertise in variant calling
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cancer genomics and functional interpretation of genetic variants. Proficiency in Python, R, or other bioinformatics languages. Knowledge of cloud computing, and high-performance computing (HPC
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, cloud computing, and distributed architectures, to enable efficient analysis of large-scale biomedical datasets. Collaborate with clinical and academic partners, both internally and externally, to ensure
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pipelines, proficiency in genomic association analyses, particularly involving large-scale datasets, and familiarity with cloud computing and/or high-performance computing (HPC) environments