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on data science and engineering. The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution earth system model data, with an emphasis on Seamless
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attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH Silvio O. Conte Center on the "Cognitive Thalamus". The successful
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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
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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
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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
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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
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of interest include: Metabolomics, isotope tracing, metabolic flux analysis, quantitative modeling, mass spectrometry imaging, cancer metabolism, small molecule inhibitor discovery, dietary impact on cancer
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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
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, molecular biology, microbiology, biochemistry, biophysics, computational modeling or related fields. Experience in metabolic engineering, synthetic biology, yeast genetics, or control theory is a plus but not