54 modelling-complexity-geocomputation Postdoctoral positions at Princeton University
Sort by
Refine Your Search
-
computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and
-
to ion beams with well-controlled energies and incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes
-
/or energy *Strong methodological and quantitative skills, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling
-
health services to Princeton University faculty, staff, and employees. An integrated, evidence-informed model guides all UHS practices and services. UHS leverages clinical encounters and prevention efforts
-
information about the lab, please visit https://mesa-lab.org/. Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging to investigate: 1) How immune cells localize
-
, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling *An interest in mixed-methods approaches, including also
-
on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to advance the use of mathematical and statistical models
-
Responsibilities: Under the direction of the Principal Investigators, the Associate will contribute to empirical modeling of the economic and security effects of climate change. In particular, the Associate will
-
specific experience in Large Language Models (LLMs), and Vision-Language Models (VLMs) Excellent programming skills (Python is required, C# and C++ is desired) Fluency in English Desired qualifications
-
of the work builds on recent publications from the laboratory, e.g. integrating language models with mass spectrometry data (https://www.nature.com/articles/s42256-021-00407-x, https://www.nature.com/articles