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seeking to hire a Full-Stack Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack
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Maximum Number of References Allowed 3 Keywords Machine Learning Reinforcement Learning Foundational Models Post-Training Large Language Models
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organizing data into a research ready form. The associate will work with senior researchers to perform statistical and machine learning based analyses including predictive modeling and real world evidence
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Machine Learning Engineer with advanced expertise to lead development of large language models (LLMs) to advance CCB’s mission to leverage data and computation to transform research and education, and to
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of References Allowed 4 Keywords research, oral health, health policy, data, machine learning, statistics
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and machine learning based analyses including predictive modeling and real world evidence generation. Basic Qualifications: MS in computer science, biostatistics, biomedical informatics or related field
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the Department of Molecular and Cellular Biology at Harvard University, we research and teach how the collective behavior of molecules and cells forms the basis of life. We are driven by a passion for discovery
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technologies such as Artificial Intelligence, machine learning, SaaS (GCP, AWS, etc) and automation frameworks. Demonstrated expertise negotiating enterprise IT contracts, including ERP/SaaS licensing, cloud
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anticipated teaching needs include: Methods: Data Science Machine Learning Artificial Intelligence Technology and Policy: Cybersecurity and Privacy Space Technology and Policy Biotechnology and Society Product
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required. This is an on‑site, campus‑based position and requires the incumbent to work from Cambridge, MA location daily. The role is fundamentally hands‑on and site‑based, with occasional computer‑based and