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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Design, develop, and implement automation and robotics solutions, including but not limited to robotic process automation (RPA), machine learning, artificial intelligence, and other advanced technologies.
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IonQ's computers will soon redefine industries like medicine, materials science, finance, artificial intelligence, machine learning, cryptography, and more. Posted figures are subject to change as new market data becomes available.
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Clemson University's Bioengineering Department is seeking applicants for a tenure-track faculty position at the Assistant Professor level in the areas of Biomedical Artificial Intelligence, Machine Learning, Biomedical and Health Informatics, or Multivariate Analysis.
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Staff-led science goals include building a world-leading computational program in research areas that potentially include, but are notlimited to, computational nanoscience, quantum information science, multi-scale materials modeling, data science, artificial intelligence, machine learning and high-performance computing.
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The Lead Algorithm/Data Architect, Artificial Intelligence – (Remote Position) at Beckman Coulter Diagnostics is responsible for executing on an established visionary direction and serve a both as a leader and technical expert, capable of growing into the lead of our Hematology Program.
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Our experts in public health, performance evaluation, and health operations solve the complex problems faced by civilian and military customers alike by leveraging advanced tools including digital transformation, artificial intelligence, data analytics, cloud enablement, modeling, and simulation, and more.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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DLH delivers improved health and national security readiness solutions for federal programs through science research and development, systems engineering and integration, and digital transformation.
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Using advanced artificial intelligence and machine-learning technologies, Cedars-Sinai Cancer Center researchers can create a computational model of the patient, known as the "Molecular Twin." Why work here.
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You will leverage your ability to design, build and deploy data solutions that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights.
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Internal Collaboration: Collaborate closely with product teams, business stakeholders, MLOps, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
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Architect and implement big data processing solutions leveraging Apache Spark for ETL, data transformation, and machine learning workflows. Collaborate with data engineers, DevOps teams, and stakeholders to ensure seamless solution integration.
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Building and maintaining ETL pipelines with large data sets using services such as AWS Glue, EMR, Kinesis or Kafka, CloudWatch; Python development experience with proficiency in Spark or PySpark and in using API; AWS Services such as AWS Lambda, Event Bridge, Step functions, SNS, SQS, S3 and MI models; Knowledge of machine learning, deep learning AMIs and natural language processing (NLP) techniques.
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The faculty members are excellent educators with practical and research expertise in machine learning, data science, artificial intelligence, information security, mobile networking, social networks, bioinformatics, etc.
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