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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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background in chemical and biological engineering, bio-engineering, molecular biology, microbiology, biochemistry, biophysics, computational modeling or related fields. Experience in metabolic engineering
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to make a career change and those with non-traditional career tracks, educational paths, or life experiences. If this environment sounds like a strong match or even an exciting challenge, we encourage you
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advanced econometric and other statistical methods. The ability to write computer programs to manipulate information, devise programs for estimating econometric models, and create and manage an active
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Models of Human Cognitive Function," and potentially seed projects supported by NAM. Candidates can read more about these core projects and funded seed projects at https://nam.ai.princeton.edu/research. In
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advance regenerative medicine. For more information about the lab, please visit https://mesa-lab.org/. Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging
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macroeconomics. The position will include a variety of tasks that provide good preparation for graduate school, such as conducting numerical analysis, solving models, managing data sets, statistical analysis
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communication skills Expertise in Generative AI: Strong background in machine learning, with specific experience in Large Language Models (LLMs), and Vision-Language Models (VLMs) Excellent programming skills
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large AI models or their applications. Current PLI projects involve work with language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and
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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