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Field
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) environments, GPU-enabled systems, and cloud-based resources for large-scale data analysis and model development. Using these rich data resources, we develop and apply advanced AI/ML methods to model tumor
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preparation and grant development. Experience with statistical genetics, bioinformatics, genomics, or computational biology. Experience using high-performance computing and/or cloud computing
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frameworks and libraries (e.g., TensorFlow, PyTorch). Ability to develop and implement AI models for business applications. Knowledge of cloud computing platforms (e.g., AWS, Azure) for deploying AI
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Max Planck Institute for Meteorology | 2 months ago
successful candidate, you will pursue this research within an international collaboration of Earth and planetary scientists and become an integral member of the Multiscale Cloud Physics Group, led by
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interaction. Diagnose and improve global storm resolving models using ground-based and satellite observations and machine learning. Perform modeling tasks using cloud resolving models or large-eddy
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position combines MLOps engineering, research software development and technical coordination across cloud, High-Performance Computing (HPC) and federated research environments. A key focus will be the
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, Biomedical Informatics or a related field. Programming experience in a language such as Python or R. Experience working in a cloud environment such as Microsoft Azure. Experience in writing grant proposals
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, biostatistics, data science, and related fields. Experience with human genomic data analysis. Professional programming skills, experience with high-performance computing, and cloud computing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
contribute to innovative projects within the NIH BioData Catalyst ( BDC ) ecosystem a cloud-based platform that provides secure access to biomedical data, analytic tools, and collaborative workspaces
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ability to work in a multidisciplinary environment. Familiarity with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC) environments. Understanding of data