Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
. - Competent computer skills; basic knowledge of Canva or Adobe Creative Cloud preferred. Preferred Qualifications: - Knowledge of accessibility best practices and standards across each social media platform
-
Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
-
: 275950536 Position: Postdoctoral Research Associate in Microfluidics, Nanofabrication, and Nanophotonics Description: The Department of Electrical and Computer Engineering has opening for postdoctoral
-
) and spatial Machine Learning (ML) models Salary and full employee benefits are offered in accordance with Princeton University guidelines. The Term of appointment is based on rank. Positions
-
/laborers, electricians, plumbers, riggers, etc. General understanding of industrial hygiene sampling procedures and principles. Proficient in standard office computer applications such as Microsoft Office
-
econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
-
-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
-
need. Apply AI and machine learning algorithms to software engineering projects in the researcher’s specific domain. Application of Domain Expertise Initiate and maintain open collaboration with
-
understanding of and attention to information security in a world-class institution of teaching, learning and research. The CISO works collaboratively with University leadership and departmental technical and
-
interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials