Professor Nathaniel Daw, together with Yael Niv and Jonathan Cohen, is seeking a postdoctoral research associate or more senior researcher to work on an NIH-funded collaborative project developing and using machine learning techniques to analyze both electronic medical record and laboratory experimental data. The project focuses particularly on the relationship between psychiatric symptoms, other chronic health data, and decision making.
The successful candidate will develop statistical and neural network software for dimensionality reduction and clustering of data, and apply it to diverse datasets. They will also have the opportunity to conduct laboratory and online studies of learning, decision-making, and their relationship to psychiatric illness. The term of this appointment is for one year with the possibility of renewal based on performance and funding. Applications from members of groups historically under-represented in Neuroscience are encouraged.
Essential qualifications for this position include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with programming (in Python or equivalent). Preferred qualifications include experience in computational psychiatry, medical informatics, machine learning, neural networks, and statistics. Questions can be addressed to Professor Nathaniel Daw, firstname.lastname@example.org. Review of applications will continue until the position is filled.
Interested applicants must apply online at https://www.princeton.edu/acad-positions/position/21363 and include a cover letter, a curriculum vitae including a publication list, and contact information of at least two references.
Princeton University is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. These positions are subject to the University’s background check policy.