Job Information
Harvard University Tenure-Track Professor in Psychology and Kempner Institute Investigator in Cambridge, Massachusetts
Details
Title Tenure-Track Professor in Psychology and Kempner Institute Investigator
School Multiple Schools - Joint Search
Department/Area Psychology/FAS, Kempner Institute
Position Description
The Department of Psychology and Kempner Institute at Harvard University seek to appoint a tenure-track professor to lead an innovative research program in the study of natural and artificial intelligence. In addition to an academic appointment within the Faculty of Arts and Sciences, candidates will be appointed as Institute Investigator within the Kempner Institute at Harvard University. Candidates should connect with experimental research on humans, as well as machine learning, computational cognitive neuroscience, or other approaches related to artificial intelligence. Our interest is less in specific topic areas and more in innovation and excellence in the applicant’s research program. We seek candidates whose research complements research already going on in the Department of Psychology (https://psychology.fas.harvard.edu/faculty) and the Kempner Institute (https://www.harvard.edu/kempner-institute/leadership/#researchers) .
The appointment is expected to begin on July 1, 2024. The tenure-track professor will be responsible for teaching and mentoring at the undergraduate and graduate levels.
Note that there are three other concurrent searches ongoing with the Kempner Institute: one joint with the Division of Science in the Faculty of Arts and Sciences; one with Computer Science; and one with Applied Math in the School of Engineering and Applied Sciences. Applicants may apply to more than one position.
Basic Qualifications
Doctorate or terminal degree required by the time the appointment begins. Candidates should have demonstrated a promise of excellence in both research and teaching.
Additional Qualifications
Demonstrated strong commitment to teaching and advising is desired.
Special Instructions
Please submit the following materials through the ARIeS Portal (https://academicpositions.harvard.edu/postings/12674) . Candidates are encouraged to apply by September 25, 2023. Please reserve Thursdays and Fridays in mid-October to early November for visits.
Cover letter
Curriculum Vitae
Teaching/advising statement (describing teaching philosophy and practices)
Research statement
Statement describing efforts to encourage diversity, inclusion, and belonging, including past, current, and anticipated future contributions in these areas.
Sample publications (3-5)
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
Talia Konkle, Search Committee Co-Chair, Department of Psychology, talia_konkle@harvard.edu
Bernardo Sabatini, Search Committee Co-Chair, Department of Neurobiology, Kempner Institute, bernardo_sabatini@hms.harvard.edu
Contact Email taliakonkle@harvard.edu, bernardosabatini@hms.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
Maximum Number of References Allowed
Keywords
Assistant, faculty, tenure track, Boston, Cambridge, Massachusetts, MA, Northeast, New England, Psychology, Artificial Intelligence, Computation, Perception, Cognition, Cognitive Neuroscience, Representation Learning, Machine Vision, Machine Learning, Natural Language Processing, Reinforcement Learning, Robotics
Supplemental Questions