69 parallel-processing-bioinformatics-"Multiple" Postdoctoral positions at Princeton University
Sort by
Refine Your Search
-
background in human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use
-
background in human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use
-
simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar/neuropixel probes and electrical microstimulation to study
-
the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine
-
fields. Candidate must have excellent computational and bioinformatic skills; abilities for developing simulation models will be highly valued; experience with ancient DNA genomic datasets is encouraged
-
: 272540364 Position: Postdoctoral Research Associate Description: The condensed matter spectroscopy group at Princeton University invites applications for multiple Postdoctoral Research or more senior
-
. The successful candidate will be expected to assist with the commissioning of a new shock tube facility and will conduct fundamental experimental research related to multiple ongoing projects, including
-
continued funding; those hired at more senior ranks may have multi-year appointments. Experience with one or more of the following is a plus: metabolomics, bioinformatics, and/or bacterial genetics
-
of decarbonization and renewable energy expansion in the U.S. The researcher will work with a group of interdisciplinary scholars across multiple institutions that includes Elke Weber and Chris Greig at Princeton
-
Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
models, and their coupling, using machine learning. The postdoc will be expected to collaborate with other postdocs at Princeton and with other members of the M2LInES project across multiple institutions