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technical skills and gain knowledge in US health policy. The position is based at Stanford University. A PhD in economics, health policy, or a related field is preferred. Duties include: * Prioritize and
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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on the position and may include: Medical, prescription drug, and dental coverage Paid vacation, holidays, and various leave programs Competitive retirement benefits, including defined contribution plans and
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, immunology, epidemiology, population genetics and mathematical modelling and involve both laboratory-based projects and fieldwork. PhD: 3-4 years full-time; 5 years part-time; MSc (Research): 1 year full-time
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Commissariat à l'Energie Atomique et aux Energies Alternatives - Groupe | Gif sur Yvette, le de France | France | 3 months ago
hardness, point defects, HAXPES, extreme environments Location: Laboratory for the Study of NanoStructures and Surface Imaging (LENSIS) at CEA Saclay, France Type of contract: PhD offer, expected start date
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health care policy and aging research. Our faculty are teachers, clinicians, and scientists with unparalleled experience who advance medical innovation and provide patient care informed by the latest
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) techniques, especially to environmental data. Proficiency in remote sensing and geospatial data analysis. Expertise in computer vision and image analysis, particularly for drone or satellite imagery
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. This position is a part of the TRANSCEND doctoral network, which comprises thirteen PhD projects (https://biomed.au.dk/TRANSCEND-network/ ). TRANSCEND is designed to develop a transdisciplinary approach
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Essential: Proficiency in fluorescence microscopy techniques (confocal, wide-field, live-cell); experience with microfluidic systems or single-cell analysis; strong background in image analysis; demonstrated
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., multi-omics, electronic medical records (EMRs), and/or biomedical imaging data, among others. AI/DL for omics-based predictive modeling, e.g., disease risk, treatment response, or adverse events. AI/DL