Sort by
Refine Your Search
-
. 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
-
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
-
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
-
statistical methods and data analysis. Possibility to participate in other SCEC research projects and contribute to the preparation of future grant proposals. Required Qualifications: Ph.D. (or expected
-
. 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
-
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
-
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
-
systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
-
development – particularly in how longitudinal study designs contribute to our understanding of human development and the psychological changes processes. The lab develops and uses novel longitudinal methods
-
(community interventions, community-based participatory research, meta-analysis and bias in research, RCT methods, causal interference, mathematical modeling, and econometrics) Policy research related