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Field
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and pain research Required Qualifications: PhD (or equivalent) in epidemiology, health data science, biomedical informatics, biostatistics, public health, or a related field. Demonstrated experience
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write manuscripts and present research work at scientific conferences. Credentials and Qualifications: PhD in Biostatistics/Bioinformatics, Data Science, Computer Science, Genetics or related field
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to lead a project related to the transport of bacteria in porous media and multiphase flow. A PhD degree in engineering or earth science is needed. 75% - Conduct laboratory experiments related
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after the review date will only be considered if the position has not yet been filled. Position description Applications for the Postdoctoral Scholars are being sought from doctoral (PhD, MD, or foreign
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that uncovers the under explored synergy between plasma and quantum physics, with the aim to break through bottlenecks in plasma technology, theoretical physics, and scientific computing. Our group culture is
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Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, bioengineering, computer science, physics, or a related field Strong scientific curiosity, motivation, and rigor Strong communication
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
opportunities for research. The potential fellow must have recently earned a PhD in exposure science, industrial hygiene, toxicology, epidemiology, public health, or other related field and is interested in cross
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
opportunities for research. The potential fellow must have recently earned a PhD in exposure science, industrial hygiene, toxicology, epidemiology, public health, or other related field and is interested in cross
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integrate in vivo mouse models and proteomics via mass spectrometry to uncover mechanisms of immune reprogramming and therapeutic response. Minimum Qualifications: PhD in Biomedical Sciences, Bioengineering
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science