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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Academic: PhD in applied mathematics, computer science, or medical physics. Scientific interests: applied mathematics
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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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Division of Social Science at NYU Abu Dhabi from individuals who have or will soon receive a PhD in sociology, social psychology, computational social science, computer science, information science, data
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or equivalent Skills/Qualifications required diploma: PhD in evolutionary genetics and/or evolutionary epidemiology - expertise in the modeling of evolutionary and demographic biological processes - expertise in
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acquisition, signal processing, and data analysis Proficiency in programming Experience in child development research, especially related to auditory processing, language acquisition, or related domains Strong
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of textile-based feedstocks, monitoring process conditions, and collecting and interpreting data. The position also includes performing chemical analyses and characterizations of both feedstocks and reaction
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motivated to explore the qubits that power the quantum information processing machines of the future? Do you want to embed qubits in scalable systems and help bring quantum technology to real-world
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health experts Data Management and Computational Work (10%) Clean, process, and manage complex epidemiological and clinical datasets Develop and maintain computational pipelines for data analysis workflows
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information is to be provided: Name, title, institute, department, email address, phone number , relationship (advisor, co-advisor, collaborator, etc.). Should include the PhD advisor as the first reference. If
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relies on the precise control of quantum information in complex systems, yet the fundamental processes that govern how information spreads, scrambles, or becomes inaccessible remain poorly understood. In