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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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are interested in these or related fields, particularly those who may bring a new technology or perspective to bear on the work in the lab. Familiarity with neural networks and/or primate electrophysiology is
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Engineering, Data Science and AI theory and practice, ensuring their co-evolution and competent adoption across disciplines to enable transformative, interdisciplinary, impactful data-intensive research
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. Qualifications and personal qualities: Applicants must hold a master's degree or equivalent education in Earth Science, Geography, Geoscience, Computer Science, or a related field. Master’s students can apply
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)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c) Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed
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an ambitious programme combining collaborative work with health researchers and the development of novel statistical methods to address complex biomedical challenges. About the role The postholder will join the
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of these technologies on clinical samples. This role offers a unique opportunity to work on translational projects that span fundamental discovery to clinical application, in collaboration with engineers, chemists
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. Today, we are ranked #2 for AI and #6 for Computer Science by US News Best Global Universities; and #8 for Data Science and AI by QS World University Ranking. A hot bed of cutting-edge technology and
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% - Ultrasound Data Collection and Data Analysis 30%-Conference Abstract and Manuscript Preparation Required Qualifications* PhD in Mechanical Engineering, Electrical Engineering, Computer Science, or related
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A