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**This Cancer Clinical Research Data Manager position is hybrid, and may require full-time onsite presence at times.** Research Data Manager (Data Aide 3) - GI The Stanford Cancer Institute (SCI) is one
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comparable field Very good knowledge of quantitative research methods in medicine or health sciences Demonstrable subject-specific programming skills (e.g., R, Python, etc.) Experience with database usage (e.g
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degree in Economics (Master of Science degree of advantage) ; Demonstrated experience in programming languages such as Stata, R or Python. Previous knowledge of Dynare, GIS and/or Matlab applications and
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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sustainability or Basic software engineering knowledge and interest in GIS Programming skills like Java, Python, Docker and knowledge of cloud resources (e.g., GCP, AWS) Analytical thinking and enthusiasm
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Information Systems & Technologies (MAGIST) program and the GIS and Geospatial Technology certificate program. As a self-supporting graduate professional degree program (SSGPDP), MAGIST operates with a lean
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diagnostics in a trauma setting, GI/GU Procedures, portable procedures, and Digital Imaging experience with wireless. CPR certification. PACS experience as well as proficient computer entry skills. Experience
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | about 10 hours ago
). • Programming skills in Python and/or C#. • Experience or training in 3D development environments, interactive graphics or immersive technologies. • Minimum English level B1 or equivalent
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supervision and be highly motivated to provide excellent care and patient advocacy. Incumbent will assist with GI/Pulmonary procedures as well as administer conscious sedation. Salary range: $56.63-$84.19
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related field Demonstrated experience in geospatial analysis (GIS) and proven skills in hydrogeological or hydrological modeling Proficiency in programming (e.g., Python) Ability to handle large datasets