Adjunct Associate Faculty, Applied Deep Learning and AI (On-Campus, Fall '26)

Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society.

The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through fourteen professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.

The Applied Analytics program is seeking data analytics professionals to serve as a part-time Associate for a graduate-level course called Applied Deep Learning and AI. This advanced course delves into deep learning, blending key elements from Statistical Machine Learning. Students will gain a solid foundation in supervised learning and other related algorithms and methods. Topics covered include Support Vector Machines, Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures, Generative Adversial Networks (GAN), and Reinforcement Learning. Practical applications will demonstrate how to prepare, train, test, and validate models. 

An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University.

Responsibilities

• Attend all on-campus class sessions, assist with instruction, lead breakout sessions, facilitate discussions.
• Evaluate, grade student work and assessments as requested by the course Lecturer.
• Monitor and address student concerns and inquiries
• Conduct office hours.

Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. 

Requirements

• Graduate degree in Computer Science, Data Science, or a related field (Completing relevant coursework such as Deep Learning, Machine Learning, and Statistics courses).
• Proficient in Python and familiar with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Deep Learning Knowledge: Strong understanding of CNNs, RNNs, LLMs, Reinforcement Learning, and model evaluation techniques.
• Hands-on experience with deep learning projects and data manipulation.
• 3 years of professional experience in a role related to applied analytics

Preferred Skills & Experience

• Strong verbal and written skills for explaining concepts clearly.
• University teaching experience in related subjects

Please submit a resume inclusive of university teaching experience.

All your information will be kept confidential according to EEO guidelines.

Columbia University is an Equal Opportunity/Affirmative Action employer.