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Field
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molecule interaction modeling, polymer physics, and statistical inference to investigate RNA structure, function, transport, and regulatory mechanisms in health and disease. AI and Machine Learning for RNA
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. Capacity to contribute to curriculum development and innovative learning initiatives. Senior Assistant Professor A PhD or equivalent doctoral qualification in a relevant discipline. Demonstrated track record
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academic institutions to translate research into viable solutions. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly
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motivated individual to join our learning and teaching activities in the Electrical, Electronic and Computer Engineering discipline of the School of Engineering and Physical Sciences (EPS). You will deliver
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in English (reading, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 3 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) | Leipzig, Sachsen | Germany | 3 months ago
research on population coding and Alzheimer’s disease Key research methods: fMRI (including 7T), MEG, virtual reality (VR), a wide variety of cognitive tasks, psychophysics, machine learning, deep neural
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tools such as machine learning, process automation, predictive/preventive analytics and artificial intelligence. This course is designed to demystify the evaluation process and give you the tools that you
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care provider productivity. They also present challenges: • New types of data, (e.g., from DNA testing) may increase risk to privacy. • For machine learning and artificial intelligence to work
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years of experience post receiving their PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural language processing