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Immunohistochemical staining preferred. Experience with sequencing data analysis preferred. Education Requirements (Essential Requirements): PhD required Work Experience Requirements (Essential Requirements): Work
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QUALIFICATIONS Education: PhD or Doctorate degree Medicine (MD) required Experience: No previous experience required Knowledge, Skills and Abilities: Learning Agility: Ability to learn new procedures, technologies
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complex data sets generated from experiments, often using bioinformatics tools and statistical methods to interpret results and draw meaningful conclusions. Publication and Dissemination: Writing and
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from assigning duties that are related to the position. Department Specific Qualifications Education: Ph.D. or equivalent degree. Qualifications: A PhD in nursing, public health, developmental science
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Application in CFD/FEA: Develop and apply AI and machine learning methods to derive more generalized and predictive models from existing CFD and FEA results. The goal is to enhance the understanding of stenting
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) and treatment as prevention (TasP) in populations who need it most. Training will also emphasize on: innovative state-of-the-science statistical and design methods, c.) community engagement through
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-time Postdoctoral Associate to join the laboratory of Dr. Rivka Stone MD PhD at the Wound Healing and Regeneration Research Program. The Stone Laboratory is engaged in two major funded areas of wound
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accurate documentation and records of data collected in accordance with the guidelines. Analyze, interpret, and synthesize data and results using scientific and statistical methods. Prepare progress reports
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, molecular oncology, drug development, and clinical trials. Department Specific Qualifications Ability to lead MS based projects with minimal oversight. Proficient in basic statistical methods and design of