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Field
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to aging. Specifically, this project will design models to develop biomarkers—particularly those related to blood vessels—to forecast clinical outcomes. This project will leverage unique datasets
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with statistical modeling (ideally Bayesian statistics) • Proficiency in Fortran, R, Python, Matlab, or ideally other common languages (e.g., C/C++) Strong computational skills Strong oral and written
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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
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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addition to core programs, members of the department also participate in the NSM college-wide Molecular Biophysics graduate training program, the Knoebel Institute for Healthy Aging, and the DU Evolution, Ecology
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trainees. Our research focuses on aging, anti-tumor immunity, and vesicle trafficking using established models, with strong translational relevance. We welcome candidates with a background in cell biology or
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activities in circuits of murine models of 22q11.2 and 3q29 deletion syndromes, two rare conditions that confer the highest genetic risks of schizophrenia. Qualifications: PhD in computational neuroscience
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to further develop the initiative. Developing the Scholar’s own research program Please note this is a two-year appointment with an expected start date of July 1, 2025. Compensation, Benefits, and Perks
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, Beyond the Standard Model phenomenology, precision calculations for the LHC and intensity frontier, overlaps of particle physics and cosmology, and lattice gauge theory. The lattice efforts span weak