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Field
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. Experience with Linux/Unix environments, cloud computing, and version control systems (e.g., Git). Additional Information: Responsibilities: Perform comprehensive analyses of microbiome sequencing data (e.g
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). Analysis will be performed on collaborative cloud computing environments using the extensive computing infrastructure developed by the Sanders Lab. You will be involved with all aspects of the data analysis
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terrain dynamics. Familiarity with cloud computing platforms (e.g., AWS, Azure) and advanced analytics. Knowledge of causal inference or complex systems theory is a plus. To Apply: Any questions can be
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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conferences and/or leading scientific journals. Excellent programming skills and hands-on experience with leading machine learning frameworks (e.g., TensorFlow, PyTorch). Practical experience with cloud
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(edge to cloud), European Data spaces, SIMPL middleware, Interoperability Frameworks (e.g. Minimum Interoperability Mechanisms (MIMs), etc) If you additionally like to create results based on knowledge
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familiarity with supercomputing or cloud platforms. Experience with AI/deep learning beyond simple tools (e.g., Random Forest, ANN), particularly in integrating physical models and AI algorithms. Knowledge
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++ and Python programming languages. Experience in open source projects, GPU programming, distributed computing and cloud computing are considered to be strong assets. The position of Research Fellow at
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and machine learning tools, primarily in Python, Web/Cloud Services and NoSQL/SQL database (MongoDB/Postgres). Additional experience in R, JavaScript, ReactJS, Mechanical Turk would be advantageous but
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction