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Field
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plus · Experience with one or more of representation learning, generative modeling, graph neural networks, transformers, or foundation model pretraining and fine-tuning is a plus
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international research networks. We also run an advanced drone lab on behalf of the entire faculty of Mathematics and Natural Sciences (https://www.mn.uio.no/geo/english/research/about/infrastructure/facilities
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instrumentation, sensors, and custom-built research tools • Develop robust and reproducible methodologies for automated synthesis, formulation, and characterization workflows, including meticulous documentation
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 days ago
transfers. the opportunity to work with world-class researchers and build networks with a diverse group of stakeholders. Generous remuneration and conditions, including 17% superannuation and a range of
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limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks Analysis”. The appointee should be prepared
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, an extensive scientific network, and an interdisciplinary curriculum about the origin and prevalence of life. The NOMIS Foundation supports and enables insight-driven science across all disciplines
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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to develop timely, accurate, and scientifically balanced responses to unsolicited medical information inquiries · Network across the Medical Affairs organization to gain a thorough understanding of
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-sensitive disease prediction supporting public health decisions in low- and middle-income countries, built on DHIS2 and the action research network of the Health Information Systems Programme (HISP) , with
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Data Analytics, including but not limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks