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, operating and scaling scientific software, AI services and data workflows across supercomputing, cloud and quantum computing environments. You will work closely with our researchers and international
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research in engineering biology. This is a broad, hands-on role at the interface of Linux systems, high-performance computing, cloud infrastructure, Kubernetes, Slurm, storage, monitoring, and
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Information Modelling (BIM), Artificial Intelligence (AI), cloud computing, IoT technologies, and real-time data analytics. Working with an international consortium of academic and industry partners, you
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Information Modelling (BIM), Artificial Intelligence (AI), cloud computing, IoT technologies, and real-time data analytics. Working with an international consortium of academic and industry partners, you
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collaborating with IT teams in implementing research technologies that include high performance computing, research networks, cloud computing, and AI/ML technologies. Equally important is an inclusive
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cloud computing platforms or Trusted Research Environments (AWS, Azure, or Google Cloud). • Experience managing large biological datasets and databases, including proficiency with relational databases
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Intelligence, Machine Learning, Data Science, Data Management, Natural Language Processing, Cloud Computing, and related computing disciplines. They will also contribute to curriculum development
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Summary: CBRAIN is a flexible Ruby on Rails framework for accessing and processing large amounts of data across a distributed network of High Performance Computing (HPC) and Cloud Computing
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, phenotype/EHR and multi-omic datasets using secure cloud and high-performance computing environments, including Hail/VDS-based workflows when appropriate. Conduct statistical genetics and genetic
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various scientific libraries and codes for HPC systems. Experience in conducting research using HPC and cloud computing resources for modeling and simulation. Extensive experience in writing proposals