Sort by
Refine Your Search
-
Listed
-
Field
-
based on satisfactory performance and availability of funding. The anticipated start date for the position is June 1, 2025.Individuals with a strong theoretical background who expect to obtain a PhD in a
-
of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. The ideal applicant will be highly motivated; good communication skills
-
to three years depending on performance and funding). Those hired at more senior ranks may have multi-year appointments. Appointments come with a highly competitive salary and $10,000 annually in research
-
://pritykinlab.princeton.edu) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
-
. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year
-
interventions. Successful applicants will be expected to participate in the activities of the Keller Center and contribute to the emerging design program. They will work with Prof. Adriaenssens (Form Finding Lab
-
human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar
-
data-driven, computational approaches. Successful candidates will be willing and able to work across a breadth of disciplines - from genomics to computer science, sociology to psychology, engineering to
-
with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. Candidates must have or (or expect to have) a
-
Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757