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Should be competent with at least one numerically focused programming environment such as Python or Matlab using the native linear algebra, image processing, and machine learning libraries.
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We are looking for a proactive self-starter with extensive expertise in data operations at scale, a deep understanding of AI, chatbots, and large language models (LLMs), and a strong commitment to continuously enhancing our machine learning data pipelines and infrastructure.
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny.
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Expertise in one or more of the following or related areas: optimization methods, hardware and electronics, machine learning tools, computational physics, and signals and systems. Expertise in one or more of the following or related areas: optimization methods, hardware and electronics, machine learning tools, computational physics, and signals and systems.
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Demonstrated experience with machine learning algorithms (regression, semi-supervised learning, deep learning, reinforcement learning, time series analysis, predictive modeling, data mining, cognitive computing.
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The Human-centered AI team in Digital Health Oncology R&D is looking for an Associate Director of Data Science to specialize in the development of novel digital endpoints using data science, statistical learning, and innovative machine learning methods on multi-modal datasets including clinical data, real world evidence, imaging, wearables, and other biomedical data sources to address patient burden.
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With its proprietary FORCE™ platform, Dyne is developing modern oligonucleotide therapeutics that are designed to overcome limitations in delivery to muscle tissue. The Clinical Data Analyst partners cross functionally to identify risk to data integrity throughout the data flow to drive quality collection for non-EDC data sources (fluid & tissue labs, digital, imaging, wearables) in Dyne's clinical studies.
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Master's Degree in Engineering, Mathematics, or Computer Science- with a focus in Process Mining, Machine Learning, Data Science, and Artificial Intelligence. Build business insights using data visualization & machine learning in applications that are used by Fortune 500 companies.
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Understand solutions including high performance computing, subject matter expertise in machine learning, artificial intelligence, bioinformatics, and life sciences among others. This includes Cisco, Commvault, Dell, HPe, IBM, Lenovo, VMWare, and many others.
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Implement machine learning and natural-language-processing (NLP) methodologies to train and deploy data-scientific models that improve, support and streamline the work of the quality engineering (QE) teams at Red Hat.*Telecommuting permitted: work may be performed within normal commuting distance from the Red Hat, Inc. office in Westford, MA.What You Will Do:Design roadmaps and write python scripts, develop python scripts and maintain high quality standards to deploy the model into production.
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Develop and refine AI models for demand forecasting using a mix of statistical, machine learning, and deep learning methods. As a Data Scientist at Global Partners, you will play a crucial role in owning development of Data Science and Machine Learning models from our vast data sources and contributing to data-driven decision-making.
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KRI headquarters, located at the NU Innovation Campus in Burlington, MA (ICBM), is home to one-of-a-kind research and test facilities for conducting activities related to cognitive and distributed RF signal processing and machine learning, unmanned and autonomous system technologies, as well as quantum materials and sensing.
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Our research interests include radio frequency (RF), machine learning (ML), cognitive electronic warfare (EW), cognitive radio, cognitive signals intelligence (SIGINT), trustworthy AI, novel learning methodologies, and adaptive decision making and control across distributed systems, among others.
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Hands-on experience with machine learning (including deep learning), and one or more of the following technical areas: computer vision and image processing, multi-modal large language models, speaker identification/verification technologies.
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machine learning jobs in Bedford, MA
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