66 algorithms-phd-"INSAIT---The-Institute-for-Computer-Science" positions at Columbia University
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on the use of Machine Learning algorithms for rapid damage assessment. Research topics could focus on: the definition and use of novel damage sensitive features, physics informed machine learning, transfer
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operations research, operations management, statistics, and economics; and it would be ideal preparation for a PhD program or other graduate study. The Staff Associate duties involve work in one or more of the
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communication skills, as well as be able to demonstrate strong creative thinking and problem-solving skills. Minimum Degree: PhD or MD/PhD Minimum Qualifications: All applicants should have excellent
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. Opportunities may exist for clinical supervision and teaching. Minimum Requirements: PhD, PsyD in clinical psychology or doctorate in a related field. NYS license required. QUALIFICATIONS: PsyD or PhD in Clinical
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program based at LDEO, and to demonstrate strong potential for effective teaching at undergraduate and graduate levels. Applicants should have a PhD in earth and environmental sciences or related field
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Qualifications MD or MD/PhD in Biomedical Sciences and/or related fields. The candidate must have a background in immunology and genetics research and commensurate clinical training and experience. Preferred
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within the Admissions department, to meet targeted enrollment goals for the School?s MBA, Executive MBA, Specialized Masters, PhD, and Deferred Enrollment programs, other future degree programs
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at http://www.microbiology.columbia.edu. Candidates should possess Ph.D., MD, or MD/PhD degrees, and are expected to develop an externally funded research program, mentor students and fellows and
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focus on teaching, research and service. Qualifications A recent PhD earned in the last 3 years and no later than the start date of the appointment, and extraordinary promise in research, are both
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to genetic, genomic, proteomic and/or metabolomic data from hospitalized children; developing predictive algorithms for in-hospital events; investigating pattens and quality of care for hospitalized children