70 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Duke University
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novel statistical methods motivated by medical research needs Solid background in causal inference and survival analysis Experience with clinical trial research, machine learning, and high-dimensional
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include teaching responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program, unless research training
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such as the Integrated Toxicology and Environmental Health Program, the Superfund Research Center, and the Center for the Environmental Implications of Nanotechnology. TERM: 1 year, with the possibility
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require self-direction and the ability to work effectively with other team members, undergraduate, graduate, and other post-doctoral researchers in the in lab. Candidates must have obtained their PhD in a
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Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency.1. A candidate may also be appointed to a postdoctoral
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system. For the meta-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine
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, gender expression, gender identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires
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many opportunities to learn new and advanced state of the art techniques and strengthen their grant and fellowship application skills. In addition, the candidate will have a broad range of local and
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-heaton-phd/ Recent Ph.D. graduates (or people about to graduate) with interest in this topic are encouraged to apply. We value diversity of backgrounds and experience, so if you aren’t an expert in all
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-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine learning is desired