223 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Princeton University
Sort by
Refine Your Search
-
Listed
-
Field
-
are for one year with the expectation of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. A PhD in Astronomy or a related field
-
of supplies, reagents and samples. Minimum Required Knowledge, Skills, Competencies, and Abilities *PhD required *Prior experience working in a research environment *Experience in working in a microbiology lab
-
UHS practices and services. UHS leverages clinical encounters and prevention efforts into meaningful opportunities for our members to learn about and adopt healthy living practices. UHS also supports a
-
. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. Requisition No: D-25-EEB-00003 PI278599096 Create a Job Match for Similar Jobs About
-
commitment to undergraduate teaching.Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program
-
in accordance with university guidelines, a taxable moving allowance, and a research allowance. PhD is required. Applicants must apply online and submit a CV, a 3-5 page (double-spaced) statement
-
benefit program to eligible employees. Please see this link for more information. Requisition No: D-26-SPI-00003 PI278807973 Create a Job Match for Similar Jobs About Princeton University Princeton
-
focus on innovation, entrepreneurship, and technology and society, is developing an emerging research and teaching program in design that embraces Princeton's commitment to the betterment of humanity
-
computational chemistry. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those
-
discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion