The Department of Biomedical Engineering at the NYU Tandon manages the graduate level course BE-GY 6473 Applied Math and Statistics for Biomedical Engineering which provides a foundation for understanding and applying statistical methods to analyze biological and medical data. Topics covered include data visualization descriptive statistics random behavior modeling normal distribution statistical inference analysis of variance regression analysis correlation analysis non-parametric statistics and survival analysis. The course includes hands-on computer lab sections for practical application of these techniques to real biological and medical datasets. By the end of this course students should be able to understand and apply various statistical methods for data summarization and visualization in biological and medical contexts choose appropriate statistical techniques for estimation hypothesis testing regression and analysis of variance select the correct statistical method based on data type and study design and utilize statistical software tools to analyze describe and display data effectively. A typical teaching load is 37.5 hours for the whole semester which includes 14 lectures computer labs (2.5 hours for each weeks lecture and lab session. More exactly the lecture and lab date / time is every Tuesday 6 pm 8:30 pm) and 1 final exam section (2.5 hours).
We presently seek an adjunct instructor who is eager to provide a solid foundation for our BME graduate students upon understanding and applying statistical methods to analyze biological and medical data in this BE-GY 6473 Applied Math and Statistics for Biomedical Engineering course. The adjunct instructors primary responsibility will be teaching. The responsibility is fulfilled by:
Delivering the lecture and supervising the lab session every week
Evaluating individual assignments and group-based lab reports and send back feedbacks to students in time (typically within a week period)
Grading quizzes and exam(s) in time (typically within a week period)
Constructing a course project and arranging the key steps well for students to follow up and complete the project
Answering students questions relevant to course content assignments labs and course project in time
We invite applicants with expertise in relevant engineering or science fields. Applicants should ideally fulfill the following qualified requirements:
Ph.D. in engineering STEM or related fields
A documented record of university teaching in graduate level engineering statistics courses.
Prior experience in course instruction student supervision or tutoring on graduate level engineering statistics courses with excellent student evaluation ratings.
Proficiency in engineering statistical key concepts principles and methods such as data visualization descriptive statistics random behavior modeling normal distribution statistical inference analysis of variance regression analysis correlation analysis non-parametric statistics and survival analysis
Profound knowledge and experience in the application of engineering statistics towards biomedical engineering fields.
Required Experience:
IC
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