Columbia University in New York City is inviting applications for an Open Rank Lecturer in Discipline or Senior Lecturer in Discipline in the Department of Industrial Engineering and Operations Research (IEOR) at the Fu Foundation School of Engineering and Applied Science.
The full-time, non-tenure-track faculty positions focus on teaching artificial intelligence (AI), including large language models, generative AI, reinforcement learning, classical AI, and multimodal AI. Successful candidates will contribute to undergraduate and graduate education, curriculum development, executive education, and industry-linked experiential learning initiatives.
The advertised annual salary ranges from US$106,000 to US$162,000, depending on the academic rank and the candidate’s qualifications and experience. Appointments are expected to begin on either 1 January 2027 or 1 July 2027. Applications are reviewed on a rolling basis, so interested candidates are encouraged to apply early.
Columbia University AI Lecturer Positions 2027: Overview
- Institution: Columbia University
- School: Fu Foundation School of Engineering and Applied Science
- Department: Industrial Engineering and Operations Research
- Positions: Lecturer in Discipline or Senior Lecturer in Discipline
- Location: New York City, United States
- Employment type: Full-time, non-tenure-track faculty appointment
- Expected start dates: 1 January 2027 or 1 July 2027
- Lecturer salary: US$106,000–US$129,000 per year
- Senior Lecturer salary: US$125,000–US$162,000 per year
- Application deadline: Rolling review; no fixed closing date specified in the announcement
- Minimum qualification: PhD or professional equivalent in a relevant discipline by the appointment start date
About the Department of Industrial Engineering and Operations Research
Columbia Engineering’s Department of Industrial Engineering and Operations Research develops research and educational programmes across areas such as operations research, data science, optimisation, and financial engineering.
The department seeks outstanding educators who can support its growing undergraduate and master’s programmes while contributing to innovative teaching practices. Its educational approach encourages experimentation, including blended and online learning environments, and connections between academic instruction and real-world applications.
The successful candidates will help prepare students to apply AI methods to complex technical, operational, and business challenges.
Research and Teaching Areas
The department is particularly interested in candidates with teaching expertise in artificial intelligence, from theoretical foundations to practical applications.
Relevant subject areas include:
Classical Artificial Intelligence: Foundational AI concepts, intelligent systems, computational reasoning, and problem-solving methods.
Large Language Models (LLMs): Modern language-model architectures, applications, evaluation, and related computational methods.
Generative AI: AI systems that generate text, images, and other forms of content, including their practical applications and limitations.
Reinforcement Learning: Methods through which computational agents learn decision-making strategies through interaction with environments.
Multimodal AI: Systems that integrate and process multiple data types, such as text, images, audio, and other modalities.
Candidates should be able to connect these areas with applications in operations research, data science, financial engineering, or related fields.
Key Responsibilities
The appointed lecturer or senior lecturer will contribute to the department’s educational mission through teaching, curriculum development, and academic service.
Responsibilities include:
- Teaching AI-related subjects to undergraduate and graduate students.
- Developing new courses and improving existing curricula.
- Contributing to executive education programmes designed for professional audiences.
- Integrating relevant theoretical and applied AI methods into teaching.
- Supporting innovative instructional approaches, including blended and online learning.
- Building relationships with industry partners and contributing to sponsored projects for experiential learning courses.
- Participating in departmental administrative and service responsibilities appropriate to the appointment level.
Candidates invited to interview will be required to deliver a 50-minute teaching demonstration on an AI-related topic.
Eligibility Requirements
Applicants must hold a PhD or its professional equivalent by the start date of the appointment. Relevant disciplines include:
- Operations Research
- Computer Science
- Information Management and Systems
- Robotics
- Statistics
- Mathematics
- Related disciplines
Candidates must demonstrate excellent teaching credentials and strong communication skills.
Requirements for Lecturer in Discipline
Applicants at this rank should have teaching experience, documented evidence of pedagogical excellence, and evidence of continued professional development and activity in their field.
Requirements for Senior Lecturer in Discipline
Applicants seeking the senior rank should demonstrate substantial professional experience and accomplishments, an outstanding record of teaching as a lecturer, and documented pedagogical excellence. They should also have experience carrying out administrative or other departmental responsibilities.
Experience with industry collaboration, blended learning, and online teaching is advantageous.
Columbia also welcomes qualified candidates who can contribute to the diversity and excellence of its academic community through their teaching, research, and service.
Salary and Compensation
The advertised annual salary ranges depend on the rank of appointment:
| Academic rank | Annual salary |
|---|---|
| Lecturer in Discipline | US$106,000–US$129,000 |
| Senior Lecturer in Discipline | US$125,000–US$162,000 |
The final salary will depend on factors including qualifications, experience, education, specialist expertise, training, and departmental budget considerations.
The announcement does not specify additional benefits or relocation support. Applicants should consult Columbia University’s official recruitment information for further employment details.
Required Application Documents
Applicants must submit their materials electronically through Interfolio.
1. Curriculum vitae
Provide an up-to-date academic CV covering qualifications, teaching experience, relevant professional activities, publications, curriculum development, and industry engagement where applicable.
2. Statement of teaching interests and plans
Explain the applicant’s teaching philosophy, subject expertise, proposed courses, and approach to teaching AI-related subjects. The statement should demonstrate how the candidate would contribute to undergraduate, graduate, or executive education.
3. List of at least three professional references
Provide the names and contact information of at least three experts in the candidate’s field. At least one reference must be able to address the applicant’s teaching ability.
Letters of recommendation will be requested at a later stage of the selection process.
How to Apply for the Columbia University AI Lecturer Positions
Interested candidates should follow these steps:
- Review the vacancy requirements and determine whether their qualifications and experience align with the Lecturer or Senior Lecturer rank.
- Prepare an academic CV highlighting teaching achievements, AI expertise, curriculum development, and relevant professional experience.
- Write a focused statement describing teaching interests and plans, including how AI concepts can be taught through theoretical foundations and practical applications.
- Identify at least three professional referees and ensure that one can provide a detailed assessment of teaching ability.
- Submit the required documents through the official Interfolio application portal.
- Review the application carefully before submitting, and monitor communications for any requests for additional information or an interview.
The university uses Interfolio Faculty Search for recruitment. Applicants receive access to a free Dossier account for submitting application materials.
Tips for Strengthening the Application
Applicants should demonstrate not only expertise in AI but also the ability to teach complex technical concepts effectively. Concrete examples of course design, innovative teaching methods, student supervision, or measurable teaching outcomes can strengthen the application.
Candidates should also explain how their expertise connects AI with operations research, data science, or financial engineering. Those with experience in blended learning, online instruction, or industry-linked projects should highlight relevant examples.
Senior Lecturer applicants should provide clear evidence of sustained teaching excellence, leadership, and contributions to departmental administration or academic programme development.
Application Deadline
Columbia University reviews applications on a rolling basis, meaning applications may be assessed as they arrive. The announcement does not specify a fixed closing date. Candidates should therefore submit their applications as early as possible for consideration for the anticipated January or July 2027 start dates.
