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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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allow users to input CDR forcing (e.g., alkalinity addition) and produce day-by-day forecasts of CO2 uptake and storage durability. The project combines physics-based modeling, machine learning, and high
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
attention to detail and quality; strong computer skills, including Microsoft Office suite (Outlook, Word, Excel, and PowerPoint); Internet proficiency; and knowledge of or ability to learn human resource
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
. Proficiency in at least two of the following programming languages: Python, R. Experience in Machine Learning and Computational RNA Biology are desirable. Hands-on experience or understanding (the limitations
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Hagenberg (50%). Job Duties: Independent research in symbolic artificial intelligence, computer algebra, computational logic, or automated reasoning with connection to machine learning Participation in
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willing to explore the links between Algorithm Design and Machine Learning Specific Requirements Physical presence is required (remote work impossible) LanguagesFRENCHLevelGood Research
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targets to treat anhedonia. Proposals that challenge prevailing assumptions, employ cutting-edge technologies, or integrate machine learning with neurobiological data are especially welcomed. Projects
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experience-driven lifelong learning. Our world-renowned experiential approach empowers our students, faculty, alumni, and partners to create impact far beyond the confines of discipline, degree, and campus
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• Trainees (postdocs and students): 45 • Research spans eight hubs—Statistical Learning & Data Science; Genomics & Genetics; Imaging; Mobile & Wearable Data Science; Epidemiology; Health Policy; Medical