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Field
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researchers focussing on modelling, estimation and prediction related to battery systems, ranging from details on micro-scale in cells to cloud calculations for fleets of electric vehicles. About the research
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may include software package creation and maintenance, data engineering, development and/or implementation of advanced statistical methodologies, and supporting research on high performance and cloud
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communication APIs ● MCP and NLP integration ● UI/UX design ● Scientific visualization ● CyberSecurity and AAI (OAuth2, Keycloak, etc) ● Cloud deployment and Kubernetes Non-Technical Skills ● Able to work in a
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, or network-based modeling of infrastructure or industrial systems. Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization
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and William Wilcock where they will have access to in-house petascale computing facilities and cloud computing allocations. They will interact widely with all the participants in the project and have
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computing and cloud-based infrastructure. A state-of-the-art UW Fiber Lab for DAS data and Pacific Northwest Seismic Network specialists in multi-sensor networks An working environment with a commitment to
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engineering skills—Python, Git, unit testing, experiment tracking—and fluency with containerization (Docker) and basic cloud workflows are expected, alongside excellent communication and cross-disciplinary
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(LLMs), computer networks/systems or wireless networks Research experiences in at least one of the fields: wireless sensor networks, IoT networks, vehicular networks, cloud/edge computing, AI systems A
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, multi-object tracking, time-series prediction, anomaly detection). · Proficiency in programming (Python required; R/Julia or others a plus) and experience with data engineering tools (SQL, cloud
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Proficiency in R or Python Minimum of two years of experience in computational biology or cancer genomics Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP) At least one first-author peer