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Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies.
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Advanced degree (PhD or MS) in Computer Science, AI, Machine Learning, or a related field. Experience with a wide range of AI techniques, including machine learning, deep learning, natural language processing, and computer vision.
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PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field with 7+ years experience , or MS with 13+ years experience, or BS with 15+ years experience. Experience with data visualization tools (e.g., Spotfire) and advanced analytics techniques (e.g., machine learning) is required.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. Center 1 (19052), United States of America, McLean, VirginiaCurrent Master's - Data Science Internship - Summer 2025Key Role DetailsThis is a full-time paid internship program spanning ten weeks from June through August 2025.
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Support efforts of the Office of Teaching and Learning by creating, curating, or identifying tools and resources to support system-wide priorities and policies as they relate to History/Social Studies, including the implementation of the History/Social Science Framework, the BPS Essentials for Instructional Equity, and the Essential History/Social Science practices.
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You will also work with scientists and with experts in data management, lab automation, molecular design, and machine learning in the Global Biologics organization to build and continuously improve data infrastructure.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. PhD in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Work with research informatics and data teams to deploy enterprise-level cheminformatics and machine learning solutions across the discovery and medicinal chemistry groups. This will include implementing machine learning methods for physicochemical property predictions as well as ADME/PK/tox endpoints.
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Experience with engineering practices for research computing (Docker, Git, and Github, code review, Linux, cloud computing)Experience with AWS and/or Bigquery and/or Google Cloud Platform (GCP)Proficiency in machine learning techniques, with a nuanced understanding of the strengths and limitations of various approaches, particularly regarding predictive and prognostic algorithms in medical research.
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Bachelor's degree from an accredited college or university in Computer and Information Science, Computer Engineering, Computer Systems Analysis, Information Cybersecurity and five (5) years of progressive information security experience across various information security/information technology risk management domains such as but not limited to application security, infrastructure security, identity, and access management, vulnerability and cyber threat management, security architecture, etc.
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The Machine Learning discipline is focused on developing the tools and supporting the delivery of process improvement and engineering through RPA solutions. Analyze and challenge current processes; identify opportunities to simplify, streamline and automate using RPA or Machine Learning tools as a subject matter expert.
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MS or PhD in Computer Science, Engineering, Statistics, Economics, Physics or related quantitative field ( e.g. Econometrics, Mathematics, Operations Research) Bachelors degree in Data Science , Mathematics, Statistics, Computer Science, or related field.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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Process and analyze large datasets leveraging state-of-the-art computer vision and machine learning techniques. Demonstrated expertise in computer vision and/or machine learning applications.
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machine learning computer science engineering jobs Title: engineering in Boston, MA
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