410 machine-learning-"https:" "https:" "https:" "https:" "https:" Fellowship positions
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engineered constructs. Learn more about the innovative work led by Dr. Chris Chen here: https://bdc.bu.edu/bdc-team/. What you’ll do: Independently conduct research on liver cell proliferation, expansion, and
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discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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equations (2) molecular dynamics calculations (3) analysis of physical phenomena by machine learning As soon as possible after March 1, 2026 (negotiable) Where to apply Website https://jrecin.jst.go.jp/seek
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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Website: https://engineering.uark.edu/ Summary of Job Duties: The Postdoctoral Fellow will continue investigation of cancer nerve crosstalk in both breast cancer and pancreatic cancer. In both projects
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, b) computational modelling, or c) machine learning. This is a complex project managing longitudinal data from a range of sources. Therefore, thoroughness and attention to detail while managing
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, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu For questions, please email mweber@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic
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. Demonstrated high level of achievement in related research productivity and academic writing. Technical skills in computer programming, algorithm development and deep learning model implementation, and practical
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to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming