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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs
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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer science, or other relevant fields and strong interest in technical and policy research
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activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers in
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Application Materials: Please send your application package as a zipped file to kseetah@stanford.edu (link sends e-mail) , with the subject line: Application for 'Integrating Natural and Cultural Data' postdoc
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interpretation of study results, and work with a multidisciplinary team to advance The Dunn Lab’s research mission. All studies will involve analysis of data from large-scale epidemiological studies that have
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to agricultural development in sub-Saharan Africa (SSA) and South Asia (SA), including small-scale producers, gender, nutrition, climate, food system risks and digital financial services. For more information about
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, including epigenome-wide association studies (EWAS) and causal inference methods. Assist data analyst in performing data acquisition, storage, cleaning, and pre-processing for large-scale, longitudinal
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statistical analysis of experimental data. The candidate will have the opportunity to collaborate with a large network of experimental collaborators at University of Oregon and at other institutions with
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Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job About the Job: 30% Lead research projects pertaining to development of large animal models of disease