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processes of the study systems of our collaborators. Core components of the research involve, among others, Bayesian hierarchical modelling, shrinkage methods, machine learning (ML) or dimension reduction
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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possible renewals, a cumulative period of four years of research fellowship intended for doctoral students. Preferential factors: Research experience in the areas of Bioinformatics and Machine Learning
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous
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systems to rapidly traverse evolutionary landscapes Evolution of complex, multi-gene phenotypes Engineering plug-and-play selection systems for continuous evolution of diverse phenotypes Learn more at How
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broad implications for how we understand and engineer life. Learn more at How to apply Applications will be reviewed on a rolling basis. In your cover letter, please clearly explain your fit, interest
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
to completion) relevant to empirical modelling (any discipline), machine learning (any discipline), inverse methods (any discipline), ionospheric modelling and/or ionospheric measurement techniques, radio
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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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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genome synthesis and artificial intelligence will enable biological design at the organism scale with implications in bioproduction, human health, agriculture, and beyond. Learn more at jzlab.bio How