Sort by
Refine Your Search
-
Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
for this position will work to develop a conservative machine-learning based sea ice model correction that can be applied to fully coupled climate model simulations. The project will involve: 1) the development of a
-
Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
performance (https://doi.org/10.1029/2023GL106776). The successful applicant for this position will work to develop a conservative machine-learning based sea ice model correction that can be applied to fully
-
The Andlinger Center for Energy and the Environment at Princeton University seeks applications for two interdisciplinary postdoctoral research or more senior research positions to analyze and model
-
The Princeton University WET LAB (https://ren.princeton.edu/) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM
-
) 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
-
, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with optimization (theory, modeling, and tools
-
optimization (theory, modeling, and tools). Candidates should apply at: https://www.princeton.edu/acad-positions/position/39361 and include a cover letter, CV (including a list of publications), research
-
. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
-
earth system model data, with an emphasis on Seamless System for Prediction and EArth System Research (SPEAR) for seasonal to multidecadal prediction and projection. The project will emphasize elements
-
, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models