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, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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Cornell University, School of Chemical and Biomolecular Engineering Position ID: Cornell-ChemE-POSTDOC [#30598, WDR-00055411] Position Title: Position Type: Postdoctoral Position Location: Ithaca
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc Position in Multiphoton Intravital Imaging
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/fractionalized phases of matter, via computational many-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating
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. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We expect you to be able
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related discipline. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We
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Postdoc Appointment Term: 2 year renewable Appointment Start Date: As early as summer 2025 Group or Departmental Website: http://www.staarlab.com (link is external) How to Submit Application Materials
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
large data set types including RNAseq, DNAseq, RIPseq, and CLIPseq. Experience in gene expression analysis, alternative splicing analysis, machine learning, and motif analysis are preferred. Candidates