353 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at New York University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 27-Jan-26 Location: New York, New York Categories: Academic/Faculty Internal Number: 180466 The LEARN LAB is seeking
-
, 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
-
, 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
-
Clinic. Responsibilities include (i) supervising law students on cases and impact advocacy projects, and serving as a mentor and role model to law students in the clinics; (ii) helping to design and teach
-
benefits , including medical, dental, and vision. To learn more about the Center on Race, Inequality, and the Law, visit http://www.law.nyu.edu/centers/race-inequality-law . Questions may be addressed
-
the area of mathematical foundations of generative AI and applications in finance. The successful candidate will have a demonstrated background in stochastic analysis and machine learning theory as
-
after one year of employment. Details and further information regarding benefits can be found here: http://www.nyu.edu/employees/benefit/full-time/Professional-Research-Staff-Code-103.html . The position
-
aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen. NYU is an Equal Opportunity Employer and is committed to a policy of equal
-
scholarly independence. Candidates with strong backgrounds in Operations Research, Machine Learning, Data Science, Computer Science, Economics, or related fields are encouraged to apply. In compliance with
-
, 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