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. Experience in the analysis of single cell RNA-sequencing and spatial transcriptomics data is advantageous, and proficiency in statistical analysis tools such as R or Python is desirable. Interested candidates
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. Participation in didactic continuing education in cardiovascular core curriculum and statistical data analysis methodology. Complete and maintain all required clinical research regulatory certifications
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Wang’s laboratory research aims to gain new knowledge in the evolution of both the human genome and the cancer genome using statistical methodologies and machine learning techniques. These two topics
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, general familiarity with Bioinformatics and statistics preferred. Team player Excellent oral and written communication. Responsibilities: Manage projects under general supervision. General laboratory
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. The methodological research may include but not limited to statistical models for integrative deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative research
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qualifications: Experience with interdisciplinary research projects Experience with computational/statistical methods Personal skills Strong quantitative and analytical skills Independent thinking, creativity
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research experience in the field of cancer genomics, although we welcome applications from candidates with diverse educational backgrounds, including computational biology, physics and (bio)statistics