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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Adjunct Lecturer, Urban Studies The Urban Studies Program at Barnard College seeks a part-time instructor to teach the following undergraduate courses during the 2026-2027 academic...
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pedagogy, makerspaces, or human-centered/educational technology research. The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited
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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Adjunct Lecturer, French The French Department at Barnard College seeks a part-time instructor to teach the following undergraduate courses during the 2026-2027 academic year. Job...
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certification, DEA registration, and NPI. Practice in accordance with New York State Nurse Practice Act and collaborative practice requirements. Maintain compliance with applicable federal, state, and
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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Associate Director, Benefits & Total Rewards Reporting to the Director of Human
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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Adjunct, English Department The English Department at Barnard College seeks a part-time instructor to teach the following undergraduate courses during the 2026-2027 academic...
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benefits as specified by Barnard College Human Resources Contact Rachel Austin ([email protected]) for more information The salary of the finalist selected for this role will be set based on a variety of
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and discretion. Excellent research, writing, and verbal communication skills. Qualifications: Bachelor’s degree in Women’s and Gender Studies or a related field in the humanities or social sciences. 1-2
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ticketing systems (TeamDynamix preferred). Experience providing remote technical support. Work Conditions: This job is an on-site, in-person role that requires face-to-face interaction with many constituents
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for analyzing and interpreting neuroscience data. The course emphasizes experimental logic, figure interpretation, scientific communication, and responsible translation from animal models to human conditions