Dear All,

I am looking to hire a postdoc to develop machine learning algorithms for large-scale publicly available MRI and behavioral data. Experience with probabilistic machine learning (aka graphical models) or deep learning is a plus.

The ultimate goal is automatic scientific discovery (see recent paper from our lab: http://www.pnas.org/content/113/42/E6535). Topics are flexible, e.g., multi-modal fusion, individual-subject brain parcellation, individual subject behavior prediction, dynamic functional connectivity, meta-analysis, neural mass modeling, multi-scale neuroscience, graph theory, mental disorder subtypes, etc.

Other details below.

Regards, Thomas

Requirements: Ph.D. in computer science, electrical engineering, statistics, computational neuroscience or related fields. The successful applicant will work with an interdisciplinary team of computer scientists and neuroscientists, and must be willing to learn some neuroscience.

Research Webpage: https://sites.google.com/site/yeoyeo02/home

Compensation: Competitive and commensurate with experience

Attraction: Perform ground-breaking research at the National University of Singapore (NUS), while enjoying the beautiful sceneries and cultures of South-East Asia. NUS is a research-intensive university consistently ranked among the top 30 universities in the world (http://en.wikipedia.org/wiki/National_University_of_Singapore#University_ran...).

Contact: Email BT Thomas Yeo (ythomas@csail.mit.edu) with your CV.

Deadline: Whenever the position is filled.