researchers whose work addresses fundamental questions in astrophysics or cosmology and engages deeply with machine learning, artificial intelligence, statistics, or data science. Successful candidates will not only use modern computational or statistical methods, but also help advance methodology, understanding, or practice in one of these areas. A particular strength of Carnegie Mellon is its breadth across both modern AI and machine learning and more traditional statistical and data-science approaches. We value research that develops and applies the methods best suited to the scientific problem, drawing on this full range of expertise. We welcome researchers working across observational, computational, or theoretical astrophysics. The successful applicant will become a member of the McWilliams Center for Cosmology & Astrophysics, a highly interdisciplinary research center with strong connections across Physics, Statistics & Data Science, Machine Learning, and other areas of Carnegie Mellon. The appointment is intended to deepen these connections at a time when major new astronomical surveys, rapidly growing simulation capabilities, and advances in AI are creating new opportunities for discovery.
Qualifications:
Applicants should have a Ph. D. or equivalent degree in Physics, Astronomy, Astrophysics, Statistics, Computer Science, Machine Learning, Data Science, or a closely related field by the start of the appointment. Evaluation will consider the strength and potential of the research program, contributions at the interface of astrophysics and the proposed joint field, the ability to work across disciplinary boundaries, and a commitment to excellence in teaching and mentoring.
