The DOLCIT Postdoctoral Fellowship Program
The Decision, Optimization, and Learning at the California Institute of Technology (DOLCIT) research group announces postdoctoral openings starting Fall 2025. Areas of interest are: decision theory, machine learning, optimization, statistics, and data-driven methods broadly construed.
DOLCIT brings together people from machine learning, optimization, applied math, statistics, control, robotics, and human-computer interaction to form an intellectual core pertaining fundamental and applied research in "Decision, Optimization, and Learning at the California Institute of Technology." DOLCIT envisions a world where intelligent systems seamlessly integrate learning and planning, as well as automatically balance computational and statistical tradeoffs in the underlying optimization problems. For more information, please visit: http://dolcit.cms.caltech.edu.
In addition, we have a strong interdisciplinary program at Caltech, AI4Science, that aims to develop and apply Artificial Intelligence to different scientific areas. Candidates with an interest in participating can specify it in their application.
As an integral part of their postdoctoral training, postdoctoral scholars may also opt to teach a course with the permission of the CMS department.
A CV, a Research Statement, and three reference letters (up to a maximum of five) are required. The Research Statement should contain a section that addresses past and/or potential contributions to diversity, equity, and inclusion (e.g., mentoring activities, committee service, research, or teaching activities). A cover letter and a Teaching Statement are optional. Applications will be reviewed starting January 1, 2025.