88 phd-in-simulation-engineer Postdoctoral positions at Conservatorio di Musica "Santa Cecilia"
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for Geographic Information and Analysis (NCGIA). Qualifications Basic qualifications (required at time of application) Applicants must have completed all requirements for a PhD Degree in Geography or a related
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transplantation and to translate this knowledge into improved treatments. Required Qualifications: Individuals with a recent MD or PhD degree with skills in computational biology, bioinformatics, biostatistics
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looking to add another motivated, ambitious, and highly qualified creative scientist with excellent written and verbal communication skills. The successful applicant must have a PhD in chemistry
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conjunction with the Basic Science and Engineering (BASE) Initiative of the Children's Heart Center at Stanford University and the Department of Genetics to work on understanding mechanisms of pulmonary
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. Prevalent TCR clones will undergo reverse engineering to deduce the peptide bound, and this information used to generate MHC tetramers to study the induction of these clones during the anti-tumor response
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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research and travel. Applicants should normally have received their PhD in the last 3 years and must have their degree in hand prior to taking up the position on 1 September 2025. The appointment will be
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based on Stanford University guidelines , and full benefits. Required Qualifications: Recently completed PhD, DrPH, MD, or other doctoral degree in a discipline related to nutrition, food systems
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technology and b) large-scale data collection in a diverse sample spanning over 250 schools across 30 states to answer three significant questions regarding the mechanisms of word reading difficulties such as
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)parameter optimization through cross-validation. Observational research methods including interpreting multivariate regression, missing data imputation, propensity score matching, and bootstrap simulations