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. The position is intentionally interdisciplinary. We welcome candidates from control theory, nonlinear dynamical systems, applied mathematics, electrical or biomedical engineering, physics, computational science
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to develop fundamental theory and methods that enable machine learning systems to be deployed in a trustworthy manner. The project spans human-AI interaction, fairness, transparency, privacy and other
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stochastic accumulation. The position will be jointly mentored by Dr. Tim Pleskac and Dr. Jerome Busemeyer, with the postdoc taking a leading role in theory development, computational modeling, and
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Position Description POSTDOCTORAL POSITIONS IN CONDENSED MATTER THEORY, CALIFORNIA STATE UNIVERSITY NORTHRIDGE One postdoctoral position in Condensed Matter Theory is available in the group
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: refining the project’s research questions, interview protocols, coding frameworks, and analytic approaches; leading one or more strands of data collection and analysis, including semi-structured interviews
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you academically in the long run. Anticipated Division of Time 50%: Conduct primary research project. This includes engaging in fieldwork, conducting interviews, coding data, writing, and giving talks
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comparable code. Energetic-particle physics or fast-ion transport modeling. FAR3d or related reduced-MHD/gyrofluid simulation tools. Integrated transport modeling using COTSIM, MMM, TRANSP, or related
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). The RAs will help us to improve an existing Python code base for creating 3D models of ancient artifacts from large datasets of 2D images. The main qualifications are prior experience working on large
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are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random network coding
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date. Experience in qualitative research theory and practice (e.g., grounded theory analysis, interaction analysis, or discourse analysis). Experience with co-design or participatory design methods