67 parallel-computing-numerical-methods Postdoctoral positions at Conservatorio di Musica "Santa Cecilia" in United States
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postdoctoral fellow with interest in organic chemistry and radiopharmaceutical development. Successful candidates will join the Molecular Imaging Program at Stanford within the Department of Radiology, Stanford
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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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different disciplines and mentors Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Sciences Postdoc Appointment Term: 1 year minimum with the option to extend
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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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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
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Substitution in the Blind; Ocular Structures and Physiology; MR Engineering and Methods Development for the Visual System. MRI experiments will mainly be conducted at research centers at the Stanford campus and
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available immediately in the Molecular Imaging Program at Stanford (MIPS). The successful candidates will join a dynamic research group focusing on the development of peptide-based therapeutics and
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implementing novel strategies for an Adult Editing System, establishing robust Cas9/gRNA delivery methods for somatic cells in adult organisms. You will collaborate closely with a dynamic, multi-disciplinary
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(GEI), a partnership between the National Center for Ecological Analysis and Synthesis (NCEAS) and The NOAA RESTORE Science Program seeks to fill two postdoctoral positions focused on addressing
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substitution in the EGFRvIII peptide significantly increases survival in an animal model of glioblastoma by enhancing proteasomal processing. We also developed robust methods to detect a new class of non