156 computer-science-intern-"https:"-"https:"-"https:"-"U.S" positions at Ferris State University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
consultation with program faculty, as well as training via the Faculty Center for Teaching and Learning. • Faculty members also have professional responsibilities which may include but are not limited to keeping
-
Participation in department, college wide and university wide committees. Prepare and teach courses in the AAS Automotive Service Technology Program and in the BS Automotive Engineering Technology
-
deadlines, and follow through on all projects. Interpersonal Skills: Demonstrated ability to build and maintain positive relationships with diverse internal and external stakeholders (donors, media, faculty
-
correspondence for review and approval of supervisor. Input, retrieve, download and output information utilizing a computer to access various software programs and systems. Interview and recommend for hire, train
-
Program Development and Management: - Develop, implement, and oversee dual enrollment programs in collaboration with high schools and career centers. - Ensure dual enrollment programs meet academic
-
of the knowledge, skill, and/or ability required. Any equivalent combination of education, training, and experience which provides the required knowledge, skills, and abilities may be considered. Equivalency
-
: N/A Term of Position: 12 Month At Will/Just Cause: At Will Summary of Position: Assist the Head Men’s Basketball Coach in all facets of the basketball program, including coordinating and directing
-
Hardware Repair • Provide hardware repair services for university and student owned computing devices which includes warranty replacement when possible. • Facilitate and assist in supporting
-
Diploma or GED equivalency. Required Work Experience: One year of work experience in a computer-related support position. Required Licenses and Certifications: A valid driver’s license. Physical Demands
-
Teaching assignment may include the following areas: machine learning; exploratory data analysis; feature engineering; AI for Everyone; special/emerging topics; data mining and analysis; business