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Field
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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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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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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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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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Associates to join our team. In this role, you will be responsible for the installation and commissioning of the newly upgraded CMS detector, as well as the analysis of CMS data. If you are driven by curiosity
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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Qualifications Candidates with pulmonary research experience are preferred. Experience in understanding big data analysis (RNAseq, mass spec/phosphoproteomic analysis, etc), pathway analysis, and cAMP
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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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, 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