37 image-processing-and-machine-learning "UCL" Postdoctoral positions at Princeton University
Sort by
Refine Your Search
-
: 285829862 Postdoctoral Research Associate - AI/machine learning for biochemistry Location: Princeton, New Jersey Salary Range or Pay Grade: $65,000-$70,000 Description The Skinnider Lab at Princeton
-
Lab seeks a highly motivated applicant with a strong background in the development, deployment and use of custom optical instruments for imaging and/or precision measurement and an interest in studying
-
in invertebrates. Specifically, the Leifer Lab seeks a highly motivated applicant with a strong background in the development, deployment and use of custom optical instruments for imaging and/or
-
: 286084265 ***REVISED*** Postdoctoral Research Associate Location: Princeton, NJ Salary Range or Pay Grade: 65,000 Description The Department of Electrical and Computer Engineering invites applications
-
searching for a computational postdoctoral research associate. The project is associated with atomistic plasma-surface interaction simulations, employing machine learned interatomic potentials (MLIPs
-
science -electrical or computer engineering -genomics -neuroscience -population genetics / genomics -sociology Expected Salary Range: Salary begins at $65,000/year and will be commensurate with experience
-
techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
-
spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational methods to discover unknown metabolites that have strong associations to experimental
-
the application of statistics and machine learning in social science. The position requires no teaching, though teaching opportunities may be provided if requested. When teaching, successful candidates will carry
-
and machine-learning potentials for planetary materials. Curating and generating large-scale ab initio datasets across wide pressureâ“temperature regimes. Designing and training advanced machine