82 learning-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at Pennsylvania State University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
team; A passion for higher education and an understanding of complex institutions; A commitment to professional development, learning, and being mentored. DDAR is supportive of flexible work arrangements
-
, training, and supervision of teaching assistants (TAs) and related administrative work 3. Selection, training, and supervision of undergraduate learning assistants (LAs) 4. Organization of graded assignments
-
agreed upon. The successful candidate will be expected to teach a variety of undergraduate courses in support of the Mechanical Engineering program, advise and mentor undergraduate students, and
-
his collaborators, Yan Li in the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project is to develop
-
teach six graduate-level courses per academic year, advise and mentor students, engage in scholarly research, and contribute to program, campus, and University service. Teaching responsibilities will
-
teaching experience is strongly preferred. Availability to teach in-person preferred. Electronically submit a cover letter, curriculum vitae, and the names, addresses and telephone numbers of three
-
printing. Hands-on lab benchwork on cell biology, immunology, and animal tumor models is a plus. Generate, analyze, and evaluate data. Present results in an organized manner. Learn new techniques and
-
interest and commitment to undergraduate teaching is essential for this position. The candidate will be expected to teach courses primarily in Statistics, as well as Pre-Calculus/Calculus sequence courses
-
whose research incorporates AI-driven methodologies. Our faculty teach undergraduate and graduate-level courses as well as supervise and mentor doctoral students. In addition, we expect our tenure track
-
candidates who can build a strong methodological research base in areas of Operations Research, including optimization, stochastics, simulation, machine learning and artificial intelligence. Applicants at all