409 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions
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reclamation pilot-scale and lab-scale systems. Conduct membrane and separation process modelling, module-scale desalination system modelling, including conventional modelling and machine learning-based
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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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proposals. Responsibilities Develop, implement, and evaluate new statistical and machine learning methods aligned with the two themes above. Lead and co-author manuscripts in statistical, machine learning
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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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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of faculty supervisor, develop novel techniques incorporating machine learning in particle physics event generators. Contribute to the development of machine learning driven techniques in the Pythia 8 event
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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
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execution and milestone completion. Job Requirements Strong background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software
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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