Tenure-track Professor in Computer Science and Kempner Institute Investigator at Harvard University in Cambridge, Massachusetts

Job Description:

Harvard University


Title: Tenure-track Professor in Computer Science and Kempner Institute Investigator

School: Harvard John A. Paulson School of Engineering and Applied Sciences

Department_Area: Computer Science and Kempner Institute for the Study of Natural & Artificial Intelligence

Position Description: The Computer Science area of the John A. Paulson School of Engineering and Applied Sciences ( SEAS ) and the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University are seeking applicants for a tenure-track position specializing in Machine Learning and Artificial Intelligence, with an expected start date of July 1, 2025.

We are particularly interested in candidates with strong foundations in deep learning, generative AI, foundational models, and LLMs, with interest to apply these technologies to one or more domains including computational biology and the sciences, NLP , and computer vision. The successful candidate will be expected to lead an innovative research program that advances our understanding of and increases innovation in AI and ML, encompassing the development of new methodologies and models.

Candidates will be welcomed into an interdisciplinary and highly collaborative environment where exploration into how principles of computation and learning in artificial systems can aid in understanding the brain and, reciprocally, how insights into brain computation can enhance artificial systems is encouraged. The successful candidate will hold a faculty position in SEAS and be appointed as an Institute Investigator within the Kempner Institute. SEAS and the Kempner Institute celebrate the multiple dimensions of diversity that each member of our community offers, including diversity of background, perspective, and lived experience.

Basic Qualifications: Doctorate or terminal degree in Computer Science, Computer Engineering, Electrical Engineering or related discipline is required by the start of the appointment.

Additional Qualifications: A record of empirical or experimental expertise in Machine Learning and a strong commitment to teaching and advising at the undergraduate and graduate levels.

Special Instructions: Please submit the following materials through the ARIeS portal (https://academicpositions.harvard.edu). Candidates are encouraged to apply by December 15, 2024; applications will be reviewed until the position is filled.

1. Cover letter

2. Curriculum Vitae

3. Teaching/advising statement (describing teaching philosophy and practices)

4. Research statement

5. Service Statement (describing your efforts to strengthen academic communities, e.g., your department, institution, and/or professional societies)

6. Names and contact information of 3-5 referees, who will be asked by a system-generated email to upload a letter of recommendation once the candidate's application has been submitted. Three letters of recommendation are required, and the application is considered complete only when at least three letters have been received. At least one letter must come from someone who has not served as the candidate's undergraduate, graduate, or postdoctoral advisor.

Contact Information: Kim LaSpina

Contact Email: klaspina@seas.harvard.edu

Equal Opportunity Employer: Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.

Minimum Number of References Required: 3

Maximum Number of References Allowed: 5


Supplemental Questions: Required fields are indicated with an asterisk (*).

1. How did you hear about this position?
   • Academic Careers online
   • Bay State Banner
   • Chronicle of Higher Education
   • Harvard Department Website
   • Higher Education Recruitment Consortium (HERC)
   • HigherEdJobs
   • Inside Higher Ed
   • Nomination Letter
   • Professional Conference
   • Professional Organization or Listserv
   • Referred by a colleague

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