1,354 computer-science-intern-"https:"-"https:" Postdoctoral positions in United States
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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: Postdoctoral Researcher - College of Engineering Position Type: Faculty Location: Villanova, PA Recruitment Type: Internal/External Applicants Work Schedule: temporary Department: 205-Mechanical Engineering
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The position is part of a new collaboration between Argonne National Laboratory, the University of Notre Dame, and UIUC, supported by the Quantum Information Science Enabled Discovery 2.0 (QuantISED
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 27-Mar-26 Location: Seattle, Washington Type: Full-time Categories: Staff/Administrative Internal Number: 30853
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and have strong computational biology skills. Previous experience with epigenome-wide assays is preferred. The successful candidate will be working in a collaborative environment with multiple faculty
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Senior Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● Doctoral Degree (or foreign equivalent) in Physics, Computer Science, Computational Neuroscience
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cognitive neuroscience across the Departments of Neurosurgery, Psychiatry, Neurology, and Neuroscience at BCM as well as the Department of Electrical and Computer Engineering and Neuroengineering Initiative
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Requisition Id 16217 Overview: The Multiscale Biomedical Systems Group within the Advanced Computing in Health (ACH) section of the Computational Sciences and Engineering Division (CSED) at Oak
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‑correction, calibration, and adaptive data‑acquisition methods to improve measurement efficiency and throughput Apply physics‑based or computational transport modeling to interpret internal material gradients