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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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learning algorithms for early damage detection, health indicator extraction, and remaining useful life prediction. The successful candidate will take a leadership role in experimental integration and data
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information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in neuroscience, psychology, psychiatry, biomedical
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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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-renowned research institute and work closely with PhD students, PostDocs, software engineers and faculty members on developing cutting-edge AI ready data management. We’re working on extending and
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advantage through coherence-driven materials design and realizing scalable, modular quantum systems. These efforts integrate vertical co-design, from materials to algorithms, and cross-platform co-design
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in signal processing and control. Your role and goals As a researcher in this project, you will work on mathematical models for describing the radio environment and to design algorithms for estimating
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collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training data to test environments, which is necessary to resolve distribution shifts, hidden confounders
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and frameworks we work on, and opportunities for applying the methods with top-notch collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training
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resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's computational resources, including the Frontier supercomputer