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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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project. The ideal candidate will have experience in yeast strain development and engineering CRISPR-based control of gene expression. This position will allow for both professional and laboratory skill
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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
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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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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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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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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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collaborate with the ARG team on developing grant proposals.QualificationsRequired qualifications:Doctoral degree in a related field, such as Architecture, Civil Engineering, Robotics, etc.Excellent track
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courses. Program faculty and senior researchers will offer mentoring to support professional development. Former postdoctoral researchers with SGS have pursued careers in academia, nongovernmental and
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health, or on economic development in the region are particularly encouraged to apply. Candidates will be expected to devote themselves to research and writing and may teach not more than one course per