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and society, is developing an emerging research and teaching program in design that embraces Princeton's commitment to the betterment of humanity through deliberative, informed, and thoughtful design
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successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine learning (AI/ML) being a major focus. Many of the laboratory's interests center
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) for Energy & Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune, and deploy LLM based tools for environmental engineering
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance
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with managing the lab and projects. We also expect that you will collaborate with the ARG team on developing grant proposals.QualificationsRequired qualifications:Doctoral degree in a related field, such
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technologies, computer vision, and perception Foundational knowledge of machine learning Experience developing custom tools and end effectors for robotic assembly Good knowledge of the CAD software Rhinoceros 3D
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commitment to interdisciplinary research are especially encouraged to apply. Responsibilities will include: - Developing a computational Artificial Intelligence form finding design framework to shape
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research positions in the following fields:1. Microfluidic and Lab-on-Chip development in a multidisciplinary lab. Candidates should demonstrate track-records in microfluidics, Lab-on-Chip, and micro
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://pritykinlab.princeton.edu) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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*Strong publication record (relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM