Sort by
Refine Your Search
-
, multidisciplinary environment, and have access to Princeton's first-class resources. In addition to leading your own research agenda, you will be required to teach or support one of the existing courses in CSML each
-
defined research and laboratory tests and experiments according to prescribed protocols and assigned schedules and developing/documenting new laboratory protocols. All these activities should be done in
-
technologies, computer vision, and perception Foundational knowledge of machine learning Experience developing custom tools and end effectors for robotic assembly Good knowledge of the CAD software Rhinoceros 3D
-
, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
-
maps of the distributions of small molecules within the cell. Determining the spatial distribution of small molecules within cells is crucial for understanding fundamental biological mechanisms, but it
-
systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and data dissemination capabilities for making high-resolution earth system
-
the development and testing of new materials. The work will involve reactor design and setup with gas flow capability and process optimization. Qualified candidates should have a Ph.D. in chemistry, physics
-
, multidisciplinary environment, and have access to Princeton's first-class resources. In addition to leading your own research agenda, you will be required to teach or support one of the existing courses in CSML each
-
to Princeton's first-class resources. In addition to leading your own research agenda, you will be required to teach or support one of the existing courses in CSML each semester of the academic year. The current
-
of interest include: Metabolomics, isotope tracing, metabolic flux analysis, quantitative modeling, mass spectrometry imaging, cancer metabolism, small molecule inhibitor discovery, dietary impact on cancer