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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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team member in the CBSC focused on ligand discovery, joining a team of dedicated computational researchers with diverse expertise ranging from structural bioinformatics to machine learning and AI. Your
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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. Interdisciplinary research is actively promoted by the Faculty of Science, fostered under the University-wide six Interdisciplinary Labs (https://interdisciplinary-research.hkbu.edu.hk/), and supported by state
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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at the CCA include: Astronomical Data, Stars & Plasma Astrophysics, Galaxy Formation, Gravitational Wave Astronomy, Cosmology, Machine Learning & Astrophysics, Exoplanets & Planet Formation, Astronomical
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periods for learning, and how individuals’ innate variations interact with experience to give rise to differences in learned behaviors. The team focuses on vocal learning in songbirds as a model system to