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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. New York City (Hybrid On-Site): $181,000 - $181,000 for Data Science PhD InternSan Francisco, California (Hybrid On-site): $191,000 - $191,000 for Data Science PhD Intern.
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The Tansey lab focuses on developing novel data science and machine learning methods that address pressing needs in cancer. Demonstrated track research record in the fields of statistics, machine learning, computational biology, data science or related field (computer science, physics, biostatistics, bioinformatics.
$100,940 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.
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Undergraduate teaching experience in core topics in Data Science such as programming, data mining, data visualization, Parallel and Distributed Computing, Machine Learning, Big Data Engineering and, Probability and Statistics will be considered an asset.
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As the Program Manager, you will own the direction of program initiatives and work with both the technical and business development teams on the execution and delivery of AI and machine learning (ML) projects.
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Candidates should demonstrate an expert grasp of knowledge in one or more of the following areas: data science, cybersecurity, machine learning, artificial intelligence, data structures and algorithms, software engineering, operating systems, computer networks, and databases, either through a record of teaching excellence, or through industrial experience.
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The Analytics Experience team, which is part of the Artificial Intelligence, Data and Advanced Analytics (AIDA) organization is responsible for the creating a seamless experience for analytics experts to harness the potential of big data, machine learning, and interactive analytics through a unified platform across the enterprise – from scientific/clinical to commercial across all Pfizer geographies.
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Direct executive Search experience within any of the following scientific domains: Computer Vision, Creative, Databases, Data Science, Economics, Databases, Hardware, Machine Learning, NLP, Optimization, Operations Research, Robotics, Security, Speech Recognition, Sustainability, UX Design or UX Research.
$150,700 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Working with data mining algorithms including artificial intelligence and machine learning techniques such as regression, decision trees, association rules, clustering, deep learning, neural networks, and Bayesian models.
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We are looking for people at the Senior Manager and Director level within the Data & Analytics + Data Science Consulting Practice with a specific focus on Machine Learning (ML) and Artificial Intelligence (AI.
$240,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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This Mid-Level Software/Computer Science Patent Associate Attorney role offers a unique opportunity to grow within a prestigious law firm in the heart of New York City while working on cutting-edge technology and providing critical patent expertise to clients.
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Creates high-performing predictive models leveraging advanced geospatial, machine-learning, and deep-learning techniques. Pay Transparency Overtime eligible: Exempt Discretionary bonus eligible: No Sales bonus eligible: No Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location.
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We are seeking highly motivated postdoctoral researchers in biomedical informatics and data science to work on projects focused on the development of biomedical blockchain, clinical predictive models, and blockchain-based privacy-preserving learning.
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Develop and execute mechanistic PK/PD models of neurodegenerative diseases, including physiologically based pharmacokinetic (PBPK), quantitative system pharmacology (QSP) models, clinical trial simulations, literature meta-analysis, machine- learning/deep learning and other state of the art quantitative techniques.
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