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Examples include Azure Machine Learning Studio, Google’s Vertex AI, IBM Watson Studio, Amazon SageMaker and open-source tools like Kubeflow. Should have knowledge of, but not expertise in, open-source high-code frameworks like PyTorch or TensorFlow, augmented AI and ML platforms, pretrained ML models and integrated AI PaaS tools.
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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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Argonne’s Leadership Computing Facility (ALCF) and Mathematics and Computer Science Division (MCS) is looking for a Postdoctoral appointee working at the intersection of scientific machine learning SciML and large-scale simulation codes.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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MUST HAVE Master’s in Computer Science, Computer Engineering or related Engineering, Machine Learning, or related field; 3 yrs relevant experience in one of the following: Machine Learning, Natural Language processing, or Ontology Engineering technologies; and required skills.
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Anatomical Kinesiology Advanced Strength and Conditioning Applied Exercise Physiology Exercise and Sport Psychology Exercise Physiology Medical Terminology for Kinesiology Majors Exercise Testing and Prescription Motor Learning Introduction Biomechanics Physiological Application of Nutrition to Exercise and Physical Activity.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Do you have a passion for invention and self-challenge? Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USABASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C.
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
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If you're interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey! Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise.
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The Data Science team leads the strategy, development and integration of Machine Learning and Artificial Intelligence. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
$140,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Master's Degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline preferred. Bachelor's Degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline required.
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Technical Expertise : Extensive experience in the complete ML development lifecycle with machine learning frameworks (e.g., TensorFlow, PyTorch and Lightning), statistical modeling, data science, and computational biology tools.
$300,000 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago
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