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(broadly defined, from school to the workplace). Demonstrates excellent written and verbal communication skills and use of rigorous, innovative quantitative and/or qualitative methods of analysis. Is
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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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uniquely cross‑disciplinary team and work closely a network of collaborators. • Jan Zimmermann — University of Minnesota • Aaron Batista — University of Pittsburgh • Kimberly Stachenfeld — Columbia
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: Familiarity with (NGS related) software tools and packages such as bwa, STAR, bedtools, samtools, Picard, RSEM, GISTIC, GATK, Strelka, Seurat Prior experience in analyzing spatial transcriptomic data. Prior
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.) and proficiency in data analysis software (such as R, Mplus, SPSS). Extensive experience interpreting research data and summarizing findings via written reports and oral presentations. Strong record
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related to protein homology modeling, ligand docking and drug design to develop the next generation of safer anesthetics. Specifically, this individual will initially be an integral developer of a large
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Qualifications: • Ph.D. in epidemiology, public health, economics, health policy, health services research, or a related field. • Strong quantitative and analytical skills, with proficiency in statistical software
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to define the immune pathways that mediate the development of anti-factor antibodies in order to develop therapeutic strategies that evade or reverse the humoral immune response and promotes factor
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Qualifications: • Doctoral degree with quantitative training (ideally in econometrics) or relevant research experience. • Strong coding skills in R, Stata, or other statistical software package. • Good