The Center for Data Science (CDS) is the focal point for New York University’s university-wide efforts in Data Science. The Center was established in 2013 to advance NYU’s goal of creating a world-leading training and research facility serving researchers, industry professionals, and students at the forefront of Data Science.

Today, CDS counts 22 jointly appointed interdisciplinary faculty and 3 full-time clinical faculty housed on three floors of our magnificent 60 5th Avenue building (https://www.google.com/maps/search/60%205th%20Avenue?entry=gmail&source=g) , one of New York City’s historic properties. It is home to a top-ranked MS in Data Science program, one of the first PhD programs in Data Science, and an undergraduate program in Data Science, as well as a lively Fellow and Postdoctoral program. It has over 70 associate and affiliate faculty from 25 departments in 9 schools and units. With cross-disciplinary research and innovative educational programs, CDS is shaping the new field of Data Science.

The primary responsibilities will be:

• teaching and coordinating three (3) entry- and advanced-level courses for undergraduates- and masters-level students in Data Science during each of the Fall and Spring semesters. This position will be responsible for teaching machine learning and programming for data science along with some subset of: computer vision, artificial intelligence, natural language processing, “big data”, and visualization

• training and evaluating teaching assistants

• advising students on their studies

• Applicants must have a strong background in Data Science and a Ph.D. in a related field such as computer science, statistics, quantitative neuroscience, and the like as well as experience in and knowledge about undergraduate and graduate teaching, learning, and curricular issues. other responsibilities related to the administration of the undergraduate and graduate programs, possibly including (but not limited to): helping with the administration of admissions to the MSDS and designing and revising curricula when required. ​​Some of these other responsibilities may lead to a reduction in course load.

  This Clinical Faculty position is not a tenured or tenured-track position. Data Science full-time clinical faculty hold renewable term contracts, initially for one year, and later three to five years in duration. Clinical faculty are eligible for promotion within the Clinical faculty ranks (Assistant, Associate, Full).

  In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $85,000 - $135,000.

  Applicants must have a strong background in Data Science and a PhD in a related field such as computer science, statistics, quantitative neuroscience, and the like as well as experience in and knowledge about undergraduate and graduate teaching, learning, and curricular issues.

  Please provide in your application:

• A cover letter indicating how the position relates to your overall career plans

• A complete curriculum vitae

• Three confidential letters of recommendation are required, including one that focuses on your teaching. Please follow the prompts in the application. Once you submit your application, an automated email with a link will be generated to your recommenders asking them to upload their confidential letters of recommendation.

• A 1-2 page teaching statement

• A teaching portfolio. The portfolio may include a list of courses taught, sample teaching materials, evaluations of teaching, certifications, or other supporting documents.

• (preferred, but optional) A 15-minute video of your teaching. Upload your video to a public streaming site (such as YouTube or Vimeo) and submit the URL with your application.

  Applicants must possess a doctorate degree or expect to have one by the start date.

  Applications received through the interfolio application page before January 31, 2025 will be given full consideration.

  Questions should be directed to cds@nyu.edu.

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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels.

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