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. Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred
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with a strong background in cognitive or computational neuroscience, with an emphasis on neuroimaging techniques and computational methods. The ideal candidate will possess not only a deep conceptual
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combinatorial panning methods, including phage and mRNA display, to identify de novo peptides for promising biomarkers lacking a natural ligand or lead structure. We then optimize peptide ligands for affinity and
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. Applicants with experience in proteomics and MS method development who are interested in applying their skills towards this challenge alongside learning more about (1) functional genomics, (2) molecular and
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most significant genetic risk factor. Individuals carrying one copy of APOE4 have approximately a 4-fold increased risk of developing AD, while those with two copies face a 15-fold increased risk
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substantial component of the work focuses on large scale empirical research in international macroeconomics and finance. The Global Capital Allocation Project (GCAP) Lab mixes data, economic theory, and
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given to candidates studying early China using analytical methods such as zooarchaeology, paleobotany, ceramic analysis, and lithic analysis. The successful candidate will be expected to: Teach one course
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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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for Biomedical Informatics Research at Stanford University. This position emphasizes conducting real-world evidence studies using various causal inference methods (e.g., target trial emulation) to examine
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science, (3) center on whole person health to reduce stigma and bias, (4) incorporate patient participatory research methods to ensure lived experiences of pain inform the clinical research outputs, (5