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Field
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molecular biology techniques. Experience with IACUC and institutional protocols. Experience with transcriptomic bioinformatics analysis (Seurat, Scenic algorithms on 10x Genomics databases). Experience with
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troubleshooting to ensure real-world readiness. Develop and implement algorithms for autonomous control, SLAM and navigation. Ensure reliable communication between hardware components and the robotic system
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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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significant role in learning in AI by enabling cognitive agents to acquire actively knowledge and skills through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and
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Learning Develop computer graphics and machine learning algorithms (e.g., SLAM and Gaussian Splatting), and evaluate their accuracy in scene reconstruction and camera trajectory estimation using videos
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of novel algorithms to analyse short tandem repeats from short- and long-read sequencing data. Knowledge of current analytic approaches for obtaining insight into the aetiology of mendelian and complex
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research with computer programming Knolwedge of data structure and algorithms, machine learning, and artificial intelligence Skills in big data analysis Additional Information Professional references will be
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of Applied Psychology. Current faculty conduct research on a wide range of topics pertaining to the future of work, including entrepreneurship, collaboration, remote working, labor markets, algorithms, machine
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in collaborative, interdisciplinary teams. Linux development skills with Python and JavaScript. Understanding of data structures and algorithms. Familiarity with web APIs such as GraphQL, REST, and
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in histology and molecular biology techniques. Experience with IACUC and institutional protocols. Experience with transcriptomic bioinformatics analysis (Seurat, Scenic algorithms on 10x Genomics