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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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magic, quantum circuits, quantum algorithms (3) Quantum many body computations, including sign problem theory, Quantum Monte Carlo method, DMRG, and machine learning Appointments of postdoctoral
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; identification of novel phases of matter through machine learning; and the development of new algorithms for the simulation of quantum matter. Applications from strong candidates with complementary interests
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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on reliability, security, and resilience of electric power systems and microgrids and stability analysis and Scientific Machine Learning (SciML) for microgrid applications. The successful candidate will be
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modeling with AI/machine learning frameworks is a plus Department Unit/Website: www.ameslab.gov Proposed Start Date: October 1, 2025 Proposed End Date or Length of Term: September 30, 2026 Number of Months
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for interacting with colleagues and stakeholders. Department Specifics: Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time