50 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs at Pennsylvania State University
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changing-look AGN/tidal disruption event/supernova host galaxy studies. Applicants with an interest in joint survey analysis methods, machine learning applications to survey data, and large-scale survey
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background in one or more of the following areas: dynamics analysis of power systems, machine learning, cybersecurity, renewable energy, microgrids, hands-on experiences on hardware-in-the-loop projects
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, and organize all data from depositions, characterizations, and property measurements. (6) Organize all data and learning into scientific manuscripts, quarterly reports, and presentations. (7) Coordinate
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interdisciplinary team. The final candidate must have a Ph.D. in Materials Science and Engineering, Electrical and Computer Engineering, Physics, Chemistry, or other comparable majors. They should have experience in
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clinicians Qualifications and Requirements: A PhD in Mechanical, Electrical, Biomedical Engineering, or related fields by the start date Prior experience in neural signal processing, machine learning, control
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REQUIREMENTS The College IST is seeking applicants for part-time job of research assistant. Job duties to include: Seeking an assistant for a research project related to data privacy/Machine Learning
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method widely used in social sciences, education, and business research. This project aims to advance AI applications in qualitative research while providing hands-on experience in machine learning
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Machine Learning, Natural Language Processing, or Computational Linguistics. Familiarity with formal logic, symbolic reasoning, or knowledge representation. Proficiency in Python and experience with AI/ML
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), and in vivo fiber photometry (TDT). We are particularly looking for a PhD-level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and their causal link
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or experience in the following areas. An interest in climate science, environmental studies, data science, or related fields. The student should be curious and ready to learn more about risk analysis! Prior