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, APIs, and SDKs by reading documentation • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. • Experience with common data
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for distributed AI training, agentic AI with modeling and simulation, and end-to-end workflow monitoring, profiling, and optimization. Working with quantum simulation tools, including NVIDIA CUDA-Q, to enable
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researchers as you co-design solutions that will enable the development and operation of new algorithms and software to solve leading-edge research problems. You will find this work exciting if you: Want
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elements distribution, crystallographic texture), mechanical properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning assisted
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Required Skills: Current or planned MS or PhD student at the University in CS or related field. Solid background and working knowledge of computer science fundamentals including algorithms, data structures
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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, computers and instrumentation hardware. Ability to install and oversee installation software algorithms for distributed controllers and maintain associated databases. Ability to coordinate maintenance and
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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range of areas including but not limited to Artificial Intelligence, Machine Learning, Data Science, Security and Privacy, Parallel and Distributed Computing, Deep Learning, Internet of Things (IoT), and
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stakeholders, both internal and external. This will involve managing multiple communications channels and planning, creating and distributing high quality content to promote the Hub’s activities and impact. This