Teaching Track

The International Society for Bayesian Analysis; Pittsburgh (Allegheny County); On-site; USD 70,000 - 120,000; Full time

Job summary

Une université de renommée mondiale recherche un professeur de suivi de l'enseignement pour un poste à plein temps. Le candidat idéal aura un doctorat en statistiques, sera passionné par l'enseignement et contribuera à l'excellence académique de l'université. Le rôle comprend l'enseignement, le développement de la matière et la recherche, avec des opportunités de carrière significatives.

Qualifications

• Doctorat requis dans un domaine pertinent.
• Capacité à enseigner et conseiller les étudiants.
• Engagement dans l'enseignement et la recherche.

Responsibilities

• Enseigner des cours de statistiques à différents niveaux.
• Superviser des projets de recherche collaboratifs.
• Développer et concevoir des programmes de cours.

Skills

Enseignement

Pédagogie statistique

Statistiques

Education

Ph.D. en statistiques, biostatistique ou apprentissage automatique

Job description

Basic Information
Position Title: Teaching Track Professor (all ranks) – Fall 2018
Location: Pittsburgh, PA
Position Type: Faculty
Position URL: apply.interfolio.com/44905

Position Description
Applications are invited for the position(s) of Teaching Professor, rank (Assistant, Associate, or Full) to be determined. The Department of Statistics & Data Science at Carnegie Mellon University (www.stat.cmu.edu) is seeking candidates with a passion for Statistics and a desire to make a significant impact on both the Department’s research and educational missions. We are looking for a candidate who will develop into a creative and effective teacher to contribute to our thriving, modern undergraduate and graduate programs. A successful candidate will be expected to have strong teaching skills, to demonstrate a thoughtful approach to statistical pedagogy, and to engage deeply in the field of Statistics through research or other means. We welcome applicants from all areas of statistics.
The Department of Statistics & Data Science at Carnegie Mellon University is world-renowned for its contributions to research on statistical theory, methods, and collaborative applied research. Current collaborative research by our faculty is helping to make fundamental advances in neuroscience, cosmology, networks, finance, genetics, public policy, high-dimensional inference, and theory and methods at the intersection of statistics and machine learning. We are also widely recognized for advancing the teaching of Statistics and for the excellence of our undergraduate program, with a large number of undergraduate majors and popular joint undergrad programs in statistics and economics, and statistics and machine learning. We also have two successful Master’s programs and a thriving Ph.D. program that attracts outstanding students from around the world.

Our faculty members are recognized internationally for their expertise and have garnered many prestigious awards and honors. At the same time, the faculty is firmly dedicated to undergraduate education. (For example, two current members of the faculty have been awarded CMU’s Ryan Award, Carnegie Mellon’s highest honor given for outstanding classroom instruction.) The entire faculty, junior and senior, teach courses at all levels. The faculty are accessible and are committed to involving undergraduates in research. The Department augments all these strengths with a friendly, energetic working environment and exceptional computing resources.
Duties and Responsibilities
Teaching faculty positions at Carnegie Mellon are unusual in the high level of both flexibility and possible career advancement they offer. This position emphasizes the Department’s educational mission (teaching, student advising, curriculum development, and supervising collaborative research projects) but also involves research and/or administrative activities. Teaching load is typically two classes per semester, but varies depending on the faculty member’s role in advising and curriculum design. Faculty are also encouraged to engage in research or other activities that contribute to the field or to society at large. This is a faculty position with a long-term career trajectory and substantial opportunities for professional development.

Qualifications
Ph.D. in statistics, biostatistics, machine learning or related area required.
Application Instructions
Apply at: http://apply.interfolio.com/44905
Applicants for this position must submit: cover letter, curriculum vitae, a statement of teaching, a statement of research, transcripts, and names and email addresses of 3-5 individuals who have been asked to provide letters of reference. Contact email: [e-mail].
Application period is September 14 – December 1, 2017.
The Interfolio Scholar Services Team is available to help if you have questions about submitting required documents. You can email them anytime at [e-mail] or call them at 877.997.8807 – Monday – Friday 9am – 6pm Eastern time.