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Project Overview We are hiring highly motivated and talented Postdoctoral Associates who are interested in advancing the state of the art in resource-efficient machine learning at the Singapore-MIT
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storage, but their widespread deployment is limited by challenges in energy density, stability, solubility, and cost of electroactive redox compounds. The PhD candidate will develop and apply machine
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learning, granular computing and knowledge discovery, machine learning, deep learning, and specifically interpretable artificial intelligence. Many innovative contributions have been achieved in theory
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public. • Ability to communicate effectively across cultural boundaries and work harmoniously with diverse groups. • Demonstrated ability to effectively teach electrical, robotics, or computer engineering
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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candidate will teach core and elective courses in biomedical engineering, with a focus on one or more of the following areas: experimental analysis and design, product design, data science, machine learning
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Science, Computer Engineering, Electronic Engineering (or related disciplines). A strong record of research quality, commensurate with career stage in AI, including but not limited to: machine learning, deep learning
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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills
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for secure and resilient systems; privacy; secure sensing and control in critical infrastructures) Candidates with a PhD in Electrical Engineering, Computer Engineering, Computer Science, or other closely