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Field
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analysis. ● Prior work on kinase or other signaling-protein conformational dynamics, phosphorylation-driven activation, or allosteric regulation. ● Familiarity with machine learning and deep learning
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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other field or laboratory instrumentation Apply appropriate behavioral, statistical, econometric, causal, spatial, machine learning, deep learning, computer vision, time-series, or mixed-methods
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data in near-term era quantum computers. Applicants with backgrounds in quantum information or particle physics are both encouraged to apply. Candidates with strong expertise in machine learning, quantum
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Description The University of Nevada, Reno is seeking a motivated and innovative Postdoctoral Scholar to join the college of Engineering. This position is available immediately and offers an exciting
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Description The University of Nevada, Reno is seeking a motivated and innovative Postdoctoral Scholar to join its College of Engineering. This position is available immediately and offers an exciting
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
world. Position Summary This postdoctoral researcher will work under the supervision of Prof. Tianlong Chen in the UNITES Lab. The focus of this position will include, but is not limited to, multimodal learning, AI
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is a learning community providing intensive, didactic, and mentored research training to postdoctoral scholars, aimed at Early-Stage Investigators (ESI) and those with disabilities, interested in