Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
results e.g.,Rshiny, d3, plotly, ggplot2. A solid understanding of statistics and experience in the implementation of machine learning and statistical inference algorithms. Experience building web
-
important clinical information, instruct the patient, relieve anxiety, and gain agreement during procedures, etc. Understand and apply Guest Relations skills and display excellent customer service skills
-
, uncertainty quantification, statistical inference, and machine learning/AI. Foster a collaborative and intellectually stimulating environment that encourages creativity and rigorous scientific inquiry. Build a
-
collaborative relationships to ensure that the overall project is progressing together and on schedule. Developing and maintaining machine learning software infrastructure for experiments, and coordinating
-
complete Computer-Assisted interviews (CAI) where verbatim responses are entered into a computer. Complete refusal conversion sample as assigned. Administer standardized physical measurements and/or
-
and with this GSI position. Please include your University Department/Program and year in graduate studies. Course Description CSC 335 - Computer Networks I CSC 275 or CSC 276 required, MTH 118 or MTH
-
opportunity to help manage the Windows Server infrastructure for ITS and U-M campus units. You will manage a mix of on-premise physical and virtual machines and cloud compute instances. You will be an important
-
-impact digital learning experiences for graduate and executive audiences. You will report to the Director of Technology Infrastructure and Support at CAI. Key aspects of your role include: Designing and
-
are senior undergraduate, graduate, or postdoc students, including those interested in gaining experience in AI and cybersecurity. Responsibilities* Design and implement machine learning techniques for web
-
medical, dental and vision coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Researching and developing novel machine learning architectures for integration across