Sort by
Refine Your Search
-
Listed
-
Field
-
to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
-
Location: Princeton, New Jersey 08540, United States of America [map ] Subject Areas: Applied Physics Quantum Optics Computational Science and Engineering Quantum Condensed Matter Theory Atomic and Molecular
-
superconductors. The successful candidate must have substantial experience in state-of-the-art ARPES and/or low temperature STM/STS techniques. Some experience with first-principle methods (FP/DFT) and/or other
-
by law. About the Gordon and Betty Moore Foundation and EPiQS Initiative The Moore Foundation believes in bold ideas that create enduring impact in the areas of science, environmental conservation and
-
and submit a CV, cover letter, and contact information for three references. All candidates are subject to the University's background check policy. Inquiries about the positions may be sent
-
considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly
-
as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries
-
positions in theory, observation and instrumentation, including (but not limited to): the Lyman Spitzer, Jr. Postdoctoral Fellowship; the Henry Norris Russell Postdoctoral Fellowship; the Joint Carnegie
-
notified of the outcome of their applications in March 2026.For more information about the Global Health Program, please visit its website at https://globalhealth.princeton.edu This position is subject to
-
about each Principal InvestigatorRabinowitz, Joshua - Major areas of interest include: Metabolomics, isotope tracing, metabolic flux analysis, quantitative modeling, mass spectrometry imaging, cancer