The Center for Brain Science (CBS) and Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University seek a tenure-track faculty member working across the fields of
computational neuroscience and a machine learning approach to AI. Please forward this information to any interested candidates.
Applications should be submitted to this site:
https://academicpositions.harvard.edu/postings/12751.
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HARVARD UNIVERSITY
CENTER FOR BRAIN SCIENCE and KEMPNER INSTITUTE FACULTY POSITION
The Center for Brain Science (CBS) and Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University seek a tenure-track faculty member to lead an innovative
research program working across the fields of Computational Neuroscience and Machine Learning to discover how brain computation can benefit artificial systems and how principles of computation and learning in artificial systems can be used to understand the
brain. Current faculty use a variety of approaches to learn how brains compute and govern cognition and behavior. The successful candidate will be appointed an Institute Investigator within the Kempner Institute and will hold an academic appointment in an
appropriate department in the life or physical sciences in the Faculty of Arts and Sciences at Harvard University. A full list of potential departments can be found here:
science.fas.harvard.edu/pages/about.
CBS (cbs.fas.harvard.edu)
fosters interactions across disciplinary boundaries—faculty from several academic departments have neighboring labs and share common research facilities and meeting space; its connections also reach out across the University. The Kempner Institute (harvard.edu/kempner-institute)
is building a community of scholars, who work across boundaries and fields to advance our understanding of intelligence, broadly speaking. Investigators will join a dynamic community of researchers to study intelligence from biological, cognitive, engineering,
and computational perspectives.
A doctoral degree in the life and physical sciences, or a related discipline is required by the time the appointment begins. Candidates should have demonstrated excellence in both research
and teaching. A strong doctoral record is required and postdoctoral experience preferred. Teaching will include offerings at both undergraduate and graduate levels.
To apply, please use this link to submit a cover letter; curriculum vitae; three-page research statement; statement of teaching and advising philosophy; statement describing efforts to encourage
diversity, inclusion, and belonging, including past, current, and anticipated future contributions in these areas; and up to three publications:
https://academicpositions.harvard.edu/postings/12751.
Please also submit contact information, including email addresses, for 3-5 people 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.
We will begin considering applications as they are received, but all materials, including letters of reference, should be submitted by October 15, 2023.
Note that there are three additional faculty searches ongoing currently with the Kempner Institute at Harvard University. One is in partnership with Psychology, another with Computer Science, and
a third with Applied Mathematics. If applying to more than one, please read the search criteria carefully.
The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up to date on CDC-recommended vaccines.
We strongly welcome applications from persons from underrepresented groups.
Harvard University 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.