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Field
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transdisciplinary initiatives. FOR ALL POSITIONS The postdoctoral associates should be self-motivated, creative, productive, and organized. Successful candidates should possess expertise in statistical programming
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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the workpackage team and collaborating with partners across Europe: data sharing, code exchange, joint publications. Your qualities You hold a PhD (or near completion) in statistics, applied mathematics, data
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Essential Qualifications Applicants require a PhD in a Biochemistry-related field Preferred Qualifications: Experience with animal behavioral studies, advanced statistics, and experimenta design
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | about 7 hours ago
experimental programs: 1) next-generation searches for neutrinoless double beta decay (0𝜈ββ) in 136Xe using liquid xenon (LXe) time projection chambers (TPCs), and 2) precision measurements of radioactive
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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at the University of Utah or Huntsman Cancer Institute. This work will not only foster new collaborations that will strengthen the University of Utah’s research programs but also produce data that are needed
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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is