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Field
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development and success of our computer science program. The successful candidate must reside in Washington State by the start of the position and demonstrate a strong commitment to teaching in person
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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courses), curriculum development, and student advising. The main responsibility of this position is teaching Computer Engineering classes. The annual teaching course load is six courses, with the potential
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novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques and interpretable machine learning methods (30%). Drive
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science, including supervising team members, developing novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques
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intelligence is preferred in candidates applying for this position. Responsibilities Design, develop, test, and debug complex software programs. Implement and optimize algorithms (ML + AI) for data-intensive
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algorithmic components and primarily programming courses with a focus on bioinformatics methods. Such graduate courses seek experienced bioinformatics, biotech, and data science professionals with a desire to
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of hardware design, cryptographic algorithms, and the RISC-V instruction set architecture (ISA). You will work closely with the AES and ASCON designers in our team to ensure seamless integration and optimal
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these insights and applications using the MTM dataset, and administers a mini-grants program to engage a wider community of researchers and EdTech developers. The work includes, but is not limited to: (1) working
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with OSL: Use OSL to implement the PPTBF algorithm in 3D environments: like a couple of point process, feature function and window function. Optimize Procedural Algorithms: Develop more efficient methods