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Field
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software program (e.g., R, STATA) Demonstrated experience accessing, preparing, and analyzing secondary data Strong interpersonal and communication skills, with the ability to collaborate effectively with
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models. • Bioinformatic analysis, R programming. FLSA Exempt Full Time/Part Time Full Time Number of Hours Worked per Week 40 Job FTE 1.0 Work Calendar Fiscal Job Category Research Benefits Eligible Yes
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(classic; Bayesian), machine learning, or other statistical approach with accompanying expertise in whatever stats package(s) is desired (SPSS; R; Stata; SAS; NumPy or PsyPy; etcetera). A strong ability to
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) and ESCH-R (Home - ESCH-R Consortium Opens external ), while also having the intellectual freedom to develop your own research lines. Working in a multidisciplinary environment, you will collaborate
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Institute e-mail: r-kolesnick@ski.mskcc.org If you have any questions about this job opprtunity, please contact: Christina Provenzano provenc@mskcc.org #LIOnsite Closing MSK is an equal opportunity and
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with statistical software, such as R, Stata, SPSS, Python Knowledge, Skills, and Abilities: Strong interpersonal, organizational, and customer service skills Maintains attention to detail and utilizes
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
, or related fields Strong programming skills in Python, R, and experience with Linux environments Demonstrated experience in processing and analyzing large-scale genomic and transcriptomic datasets
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, and a demonstrated ability to collect, organize, and analyze data using R or SAS. The candidate selected for this position must be able to meet eligibility requirements for work in the United States at
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, bioinformatics, molecular biology, toxicology, pharmacology). 2. Proficiency in bioinformatics, programming, and tools for the analysis of large genomic datasets and single-cell dataset, including R, linux, python
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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