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Knowledge of CFD, Fluid Dynamics, experience working with models (either Atmosphere or Ocean) is required, and knowledge of python and deep learning algorithms is preferred. Modeling will involve integrations of the models with satellite observations, sensor data and UAV data.
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We are looking for a Sr. QA Automation Engineer - Bixby who will be responsible for expertise in AI, large scale data analysis, statistical analysis, deep learning, computer vision, robotics and language understanding to join us.
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Deep understanding of emerging trends in digital innovation, such as artificial intelligence, machine learning, blockchain, augmented reality, or IoT. Data Management and Analytics: Oversee the collection, integration, and analysis of large-scale scientific data sets, from the lab to the trials, utilizing advanced analytics and machine learning to extract valuable insights for drug discovery and development.
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Technical Proficiency: Combine your deep understanding of machine learning, statistics, and data science with practical experience in programming languages such as Python or R. Experience in working with AI technologies and tools, such as natural language processing (NLP), AI generation, machine learning algorithms, deep learning, etc.
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You may possess a vast background (additional certificates help support your deep security knowledge (CISSP, GSEC, CISA, CISM, CRISC, MCSD), comprising of functional experience working in a global hybrid cloud environment, including AWS, Azure, O365, and GCP. Experience with Data Governance or Data Compliance Standards is valuable.
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The team at Katanemo built serverless compute at AWS, deep learning infrastructure for Bing commerce, the data and infrastructure stack at Cloudera and Lyft and is bringing their expertise to bear for builders creating new AI-native apps.
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Our Vision: Empowering Cornell’s research and learning community with deep expertise, innovative services, and outstanding collections strengthened by strategic partnerships. Reporting to the Director, Research Data and Open Scholarship (RDOS), the Research Data Librarian helps support Cornell University researchers throughout the research data lifecycle to meet their planning, management, analysis, sharing and archival needs.
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This position is available to individuals with research interests in applications of machine learning and artificial intelligence to wearable sensor data for nutrition research. Extensive practical experience and strong foundation in machine learning and deep learning (Python, TensorFlow or Pytorch.
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Utilize methods in the areas of Artificial Intelligence (AL), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) to design and implement data solutions.
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Participate in partnerships with data science leaders, like our partnership with NVIDIA to deliver Deep Learning Institute (DLI) training to the federal government. Experience with training deep learning models for computer vision or natural language understanding using frameworks, including TensorFlow, PyTorch, or Keras.
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Deep familiarity with the security requirements of some combination of Microsoft Active Directory, Microsoft 365, Windows and Linux Servers, Meraki Networks, Salesforce, AWS Cloud Hosting, Financial and Human Capital Management Systems, Application Development, Student Learning Management Systems, Data Warehouses and Enterprise Identity and Access management (IAM) systems required.
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Five (5) years of experience must include: Informatica AXON; EDC; IDQ; Collibra; Implementing Data Quality frameworks, metadata management solution and data governance solutions; AWS, big data technologies, python and databases; Overseeing projects and programs with a focus on delivery; Data management; Data Governance strategy; Presentation Skills; Software Design and Architecture; Project/Program Management; Stakeholder Management.
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Also requires two (2) years of experience in each of the following: modeling tools and frameworks including Python, R, TensorFlow, Keras, PyTorch, Databricks and PySpark; Azure, GCP or AWS cloud infrastructure; data modeling/analytics with SQL, Snowflake and Tableau; dataanalytics for healthcare industry products or services; machine learning methods including regression, decision trees, and deep learning; and statistical modeling for business intelligence.
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Looking for experience with the following: DevOps, CI/CD, Docker, Kubernetes, AWS Sagemaker, GenerativeAI (GenAI - ChatGPT), Large Language Models (LLM), Natural Language Processing (NLP), Neural Network (NN, CNN), Deep Learning.
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OverviewTransaction Network Services (TNS), a subsidiary of Koch Industries, is seeking a skilled Senior Data Scientist to join our AI Labs. This role involves analyzing complex datasets, developing statistical and deep learning models, and implementing advanced machine learning solutions.
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