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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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The Princeton Center for Statistics and Machine Learning (CSML) invites applications for DataX Postdoctoral Research Associate positions. The DataX Postdoctoral Research Associate positions
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Proteomic and metabolomics analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job
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skills, proficiency in quantitative analysis of large datasets and working with pre-trained machine learning models is desirable but not essential To apply online for this vacancy and to view further
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for an individual to be appointed as a postdoctoral associate under the supervision of Prof. Mark Tuckerman. The research will focus on the use of classical and quantum molecular simulation and machine learning
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: Postdoctoral Position Location: Taipei, Taipei, Taiwan Subject Areas: Physics / Biology , Biophysics , Chemistry , Computational physics , Condensed Matter Physics , Machine Learning , Nanotechnology
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum
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of virtual reality for research related to human ambulation, balance and gait analysis. The candidate must have prior research experience with virtual reality, computer graphics and animation, gaze detection
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will