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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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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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., geography, urban planning, data science, sociology, public health, emergency management). Ideal applicants will have: *Expertise conducting spatial and statistical analyses *Experience with scientific
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Qualifications Experience in electrophysiology and analytic methods for analyzing this type of data. Experience in computational neuroscience and modeling, as well as in the aging brain is desirable. FLSA Exempt
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. Contribute to grant writing. Minimum Qualifications PhD in computer science, computational biology, or related field. Dissertation must have focused on development of neural networks for analysis of proteins
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(e.g. Presentation, PsychoPy, E-Prime, Gorilla). You have experience in data analysis, visualisations and programming in R and/or Python. You have experience with statistical models (e.g. mixed-effects
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candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in Mathematics, Statistics
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Job Description Required Qualifications: (as evidenced by an attached resume) Ph.D. (or foreign equivalent) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related field
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to develop robust experimental designs, to conduct data processing and statistical analysis with relevant programming language(s) (such as Python and R), and to handle high-dimensional research data to a high
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Ph.D. (or foreign equivalent) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely