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of the project examine the changes in students’ peer networks and quality of relationships with key significant others (i.e., peers, parents and teachers), the influence of students’ peer networks attributes and
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: FastTrackAI: Fast-Tracking AI for Scientific Discovery with Accelerated Networking and Computation on Modern Architectures in Singapore Project Introduction: The advancement of accelerated computation and
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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the Cornell Career Network. These offices, both located in Barnes Hall, work in close partnership to support students, collaborate on initiatives, and share operational resources. University Career Development
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focus on distributed acoustic sensing on pre-existing telecom fiber networks, wavefield analysis, structural and geophysical interpretation, multi-modal data fusion, and lab-scale and field experiments
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telecom fiber networks. The role will focus on ambient and anthropogenic seismic noise for urban subsurface characterization, seismic source characterization, geophysical imaging, and environmental
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, researchers, and students within the international research network, while supporting the supervision and mentoring of postgraduate students. This position offers an opportunity to contribute to cutting-edge
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innovations and provide professional services. We are looking for a Research Fellow to work on an on-going project on risk analysis of subdaily rainfall events. The role will focus on rainfall network and
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, tsunamis, and climate change in and around Southeast Asia, towards safer and more sustainable societies. EOS maintains a regional network of geophysical observation stations in collaboration with neighboring
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Conduct research in adversarial machine learning, AI security and the robustness of deep