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Field
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community engagement activities to aid in recruitment and retention Preferred Qualifications Equipment Utilized Proficiency with statistical software (e.g., R, MPlus, SAS, SPSS) Physical Demands and Work
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, decentralization and mission execution. The RAI team has a strong European participation in multiple R&D&I projects, while RAI was also participating in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA
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: Minimum Qualifications: Applicants must meet minimum qualifications at the time of hire. PhD in biostatistics, statistics, or related field Experience using R and/or Python to carry out data analysis
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commercial and primary cells, and familiarity with the design and execution of preclinical trials. R&D Project Management: Experience in writing, managing, and executing research and development projects
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biomedical sciences, bioinformatics, clinical research or related field strong clinical trial experience (design, execution, and regulatory submissions) proficiency in bioinformatics, statistical analysis (R
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oncology-specific NLP models with peer-reviewed publications is preferred. Strong quantitative skills are mandatory, including analysing large-scale databases (e.g., Hospital Authority EHR) using R/STATA/SAS
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assessment and supervise/mentor students Programming skills (e.g. Python, R, MATLAB, C) are seen as a benefit. What we offer The salary of the postdoctoral researcher will be based on level 5 of the demands
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equivalent) in hand by September 1, 2025. Experience using advanced statistics to answer ecological questions, programming in R, Matlab or other statistical languages. Preferred Qualifications: Ph.D
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. Software and programming experience may include: R, STATA, Esri Arcmap, python, Leaflet, PostgreSQL, CSS, JavaScript, JQuery, Bootstrap, PHP, QGIS, PostGIS, Mapserver, Tableau, Openlayers, Geoserver, R Shiny
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statistical methods (e.g., HLM, SEM, non-linear dynamical systems) and programming skills (e.g., R, Python, MATLAB) as well as data mining techniques for analyzing performance outcomes, self-report measures