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Postdoctoral Associate in Data Analysis
Weill Cornell Medicine - Qatar
Doha, QatarQAR 5,250-12,600/moToday
QatarScience ResearchFull Time
Skills Required
PythonExcelMachine LearningData AnalysisErpCommunication
Job Description
Job: Postdoctoral Associate in Data AnalysisWork Location: QatarWork Days: Sunday-ThursdayClassification: Full TimePosting End Date: 04/19/2026Position SummaryThe position is responsible for analyzing datasets generated by cores in methylation, metabolomics, and proteomics. The focus of this role is to apply advanced analytical and computational approaches to characterize complex diseases through the integration of multi-omics modalities.Job ResponsibilitiesFormulates hypothesis independently and performs comprehensive data analysis of methylation, metabolomics, and proteomics datasets.Develops and implements bioinformatics pipelines for multi-omics data integration.Interprets results and identification of biomarkers or molecular signatures associated with complex diseases.Collaborate with core members, investigators, and external partners to ensure high-quality data processing and analysis.Prepare reports, visualizations, and scientific manuscripts summarizing findings.Writes and publishes articles in peer-reviewed journals that highlights research findings.Present research results in internal meetings and external scientific conferences.Maintains accurate documentation of analytical methods, results, and project progress.Researches articles with respect to the assigned study, keeps up to date with the latest developments and identifies areas of improvement.Performs other duties as assigned.Education and ExperiencePhD in Bioinformatics, Computational Biology, Biostatistics, or a relevant post-qualification experience.Licenses and CertificationsORC ID, SCOPUS ID, or equivalent is a must.3 publications in PubMed are a must.Knowledge, Skills and AbilitiesDemonstrated experience in the analysis of large-scale omics datasets (e.g., methylation, metabolomics, proteomics).Strong programming skills in R, Python, or related analytical tools.Familiarity with statistical and machine learning approaches for multi-omics integration.Excellent written and verbal communication skills.Ability to work collaboratively in a multidisciplinary research environment.Weill Cornell Medicine-Qatar was established in 2001 as a partnership between Cornell University and Qatar Foundation (QF). The first medical school in Qatar and a pioneer of coeducation at the university level, WCM-Q offers an integrated Six-Year Medical Program that incorporates pre-medical and medical studies and leads to the Cornell University M.D. degree.Teaching is by Cornell and Weill Cornell faculty, including physicians at Hamad Medical Corporation (HMC) who hold Weill Cornell appointments. Enrollment has grown rapidly from 25 first-year pre-medical students in the fall of 2002 to over 300 students from more than 30 countries today.WCM-Q is part of Weill Cornell Medicine in New York City, which was founded over 100 years ago, and shares the same mission:to provide the finest education possible for medical studentsto conduct research at the cutting edge of knowledgeto improve healthcare both now and for future generationsto provide the highest quality of care to the communityWCM-Q’s home city is Doha, a thriving cosmopolitan metropolis with a culturally diverse population, a rapidly growing economy, and modern infrastructure. WCM-Q is a member of Qatar Foundation, a not-for-profit organization with multiple centers focused on education, research and innovation, and community development. WCM-Q is located within Education City, the flagship development of QF, which occupies more than 12 square kilometers and is home to some of the world’s leading educational institutions, including Hamad Bin Khalifa University, and overseas campuses of elite universities, such as VCUarts Qatar, Texas A&M University at Qatar, Northwestern Qatar, Georgetown University in Qatar, Carnegie Mellon University in Qatar, and HEC Paris in Qatar.Weill Cornell Medicine-Qatar is an Equal EmploymentOpportunity/Minorities/Females/Disabled employer.#J-18808-Ljbffr
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