50 modelling-complexity-geocomputation Postdoctoral positions at Princeton University
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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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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
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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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, 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
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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 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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their potential to explore, discover and understand emergent behavior of complex quantum matter. The Moore Postdoctoral Scholars in Theory of Quantum Materials program is an integral part of EPiQS and supports
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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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, 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