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Deep understanding of NLP, LLM, deep learning, machine learning, ontology, knowledge graph, and reasoning. PhD in Computer Science, Information Science, or related STEM disciplines with extensive research in NLP, deep learning, knowledge graph, and reasoning, or Master's Degree in the same areas with 10 years of relevant professional experience.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. You'll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences, and building close-knit relationships across the company.
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The T&D team is seeking a Learning & Development Manager, Early Career to be responsible for the oversight, creation, and execution of leadership programming, in conjunction with the Global Head of Talent & Development.
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This position requires a strategic mindset and a deep understanding of best practices in workplace learning and performance. Learning Governance: Convene major content and learning providers at Dana-Farber to set policy and practice for how the compliance, policy, technical, functional, managerial, and job-related learning needs of the community will be met.
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Convene major content and learning providers at Dana-Farber to set policy and practice for how the compliance, policy, technical, functional, managerial, and job-related learning needs of the community will be met, and how the shared learning management system will be administered and used.
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Working closely with Associate Professor Jessica Lasky-Su, and Research Operations Manager will be responsible for integrating multi-omic data (genomics, epigenetics, proteomics, transcriptomics, metabolomics, electronic health record data) from both clinical data and research population, using advanced computational methods such as deep learning.
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If you are dedicated to advancing learning through digital pedagogy and have a deep understanding of evidence-based teaching strategies, especially in online learning, this role offers a unique opportunity to drive positive change in education.
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As a Software Development Manager for the AEC Solutions group, you will lead your team to build data pipelines to power our work in artificial intelligence, deep learning, generative AI, machine learning, reinforcement learning, information retrieval, and natural language processing.
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Deep understanding of industrial drug discovery including understanding the role of AI, machine learning and other computational approaches at scale to transform drug discovery. Strong exposure (either professionally or through personal curiosity and independent study) to advanced computational approaches (including AI and machine learning) is required.
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Regularly provides advice and expertise to general education teachers and the school community to support the creation of appropriate and effective academic, behavioral, and social/emotional learning experiences for students.
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In collaboration with the Senior Director of Clinical Services and Social-Emotional Learning and other OSS leaders, develop and implement programs that support students’ academic and social-emotional learning.
$158,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Deep knowledge of Eagle PACE, FactSet, APX, Archer, Bloomberg PORT+, Bi-SAM, and Morningstar are considered strong assets. Bachelor's degree in finance, Statistics, Business, or a related field; advanced degree or relevant certifications (e.g., CFA, CAIA, FRM, CIPM) preferred.
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Rope access experience or an interest in learning rope access techniques (SPRAT, IRATA). Actively engages multiple perspectives when solving problems, seeks to learn from peers, and encourages reciprocal learning among team members.
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This role requires expertise related to machine learning, multi-omics data analysis & integration, database design, next-generation sequencing (NGS) data and a background with protein-based drug modalities.
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Master’s degree in Data Science, Bioinformatics, Computational Biology, Machine Learning, Statistics, Mathematics, Physics, and 3+ years of professional experience. The successful candidate will work at the interface of data analytics, data mining, statistics, bioinformatics, and machine learning with broad impact across early discovery, candidate development, and biomarker discovery.
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deep learning jobs Title: machine learning engineer Company: Amazon in Boston, MA
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