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We are looking for a Senior Data Scientist to build and deploy Natural Language processing (NLP) models utilizing a variety of Machine learning and deep learning techniques.
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Use data science methods, including but not limited to Artificial Intelligence/Machine Learning (AI/ML) approaches, to perform data processing (e.g. filtering), feature recognition, alarm threshold determination, pattern matching, statistical trending, scoring of detection quality, and integration of other information into decision making.
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Hydroinformatics - Motivated by the expansion of data acquisition systems and the need for managing and using massive datasets, this position requires specialization in information systems and technology for water management, engineering, and operations, with expertise in extreme data management, analytics, data mining, large dataset access, remote sensing, artificial intelligence, machine learning, water systems modeling, and geographic information systems.
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We seek applications from established investigators for positions in both the tenure-track and clinical/research/teaching track with particular emphasis on climate change, environmental justice, environmental epidemiology, planetary health/one health, environmental -omics, implementation science, policy and communication, and data science, machine learning and artificial intelligence applications in environmental health.
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PSC advances science across a wide spectrum of fields including artificial intelligence / machine learning, medical imaging, weather modeling, cell biology, and genomics. Master’s or PhD degree required, with preferred education/experience in Biology, Biomedical Informatics, Biomedical Engineering, Computational Biology, Computer Science, Data Science, AI/ML, or related fields.
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Collaborate with other Technologists within Teledyne FLIR on application of AI/ML to system level data fusion, e.g. combining CBRNE sensor outputs with other information in Augmented Reality/Virtual Reality (AR/VR) or other situational awareness modalities.
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This role is responsible for planning and executing on key data engineering initiatives spanning our work in artificial intelligence, machine learning, search, natural language processing and product analytics.
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Research Scientist / Computer Systems Researcher - Entry to Expert Level (Maryland) NSA Research Scientists are actively expanding the boundaries of what can be accomplished with artificial intelligence, machine learning, human-machine teaming, software reverse engineering, data science, novel architectures, cyber security, high performance computing, and computational linguistics.
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure)Ability to interact at all levels of the client organization, build consensus and foster changeAbility to work independently, manage small engagements or parts of larger engagementsExperience with pre-sales, proposals and RFP activitiesSuperior critical thinking, analytical and problem-solving skillsWillingness to mentor and counsel junior staff.
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure) Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
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Experience applying data science techniques, including time series, supervised learning (e.g., regression analysis, classification analysis, univariate models, multi-variate models), and/or unsupervised learning (e.g., clustering, association, dimensionality reduction), to Finance use cases such as forecasting and predictive analytics.
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You will work with researchers at the University to apply artificial intelligence (AI), machine learning (ML), and deep learning (DL) to the researchers’ data.
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Skilled in Prompt Engineering and AI chatbot/user facing applications with features such as search, translation, and summarization. Skilled in data collection and preparation, analysis, interpretation, and predictive modeling approaches to test and validate statistical drivers.
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Knowledge of generative AI implementation challenges including data quality, model biases, cost management, cyber security, and strategies to address them. Bachelor's degree in a relevant field (e.g., Business, Computer Science, Data Science, or equivalent experience) from an accredited university.
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The team's work is essential in supporting feature developments that use artificial intelligence and machine learning including Bloomberg Law's Docket Key, Points of Law, Brief Analyzer and Draft Analyzer, Bloomberg Tax's search capabilities and Bloomberg Government's State Bill Comparison.
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