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, including annotated electronic resources and application of statistical analysis and bioinformatic pipelines. The candidate will be expected to contribute to other group activities, such as, but not limited
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data analysis (e.g., MRI preprocessing, statistical modeling, familiarity with tools such as FSL, SPM, AFNI, or similar platforms). Proficiency in statistical programming (e.g., R, Python, MATLAB
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background in experimental design, data analysis, and scientific writing. Proficiency in statistical software (e.g., R, SPSS, Python) and survey tools (e.g., Qualtrics). Ability to work independently and
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the start date of the appointment. Demonstrated expertise in quantitative data analysis, including advanced statistical modeling (e.g., mixed-effects models, longitudinal analyses, mediation/moderation
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cancer populations Research methods/design Basic statistical analyses Cognitive-behavioral therapy knowledge or experience Acceptance and commitment therapy knowledge or experience Research publications
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for this Postdoctoral Scholar position, candidates must possess a Ph.D. in Neuroscience or relevant field requires applicants to demonstrate strong research skills, data analysis proficiency, and statistical expertise
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in life cycle analysis for separation science are required. Desired: Research interest in statistical data analysis is desired. Strong software skills in Excel and Minitab or other statistical
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Qualifications PhD in Mathematical Economics and Social Science Candidates should have experience in at least one of the following areas: Statistical programming and data analysis using R, Python, or Matlab
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methods, advanced statistical techniques, and other areas. Responsibilities of the successful candidate include but are not limited to: Leading experiments focused on tobacco and cannabis product emissions
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, precision oncology, biomarker discovery, and translational cancer biology using cutting-edge computational, statistical, and multi-omics approaches. The Postdoctoral Scholar must be an expert communicator