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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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Currently pursuing a degree in Data Science, Statistics, Computer Science, Economics / Econometrics, Chemical Engineering, or related field with an emphasis on machine learning or statistical methods for data analysis.
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Experience with one or two of the following: MLOps, Deep Learning methods, NLP, computer vision, sentiment analysis, topic modeling and graph theory, and databases. Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modeling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred.
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We are looking for adjunct faculty who can teach Graduate and Undergraduate courses in Information Systems and Technology (General IT, Software Development/Programming/Software Engineering Management, Data Management/Cloud Administration/Database, IT Project Management/Information Systems Management, Networking/Network Administration/Enterprise Network Management, Cybersecurity/Information Assurance/IT Security/Computer Security or Forensic Management.
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Stay current with the latest advancements in image processing, computer vision, and machine learning technologies, and apply cutting-edge techniques to solve challenges in NGS.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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We combine expertise across multiple fields: high-performance scientific computing, physics-based modeling and simulation, data science, machine learning, applied mathematics, optimization, statistics, decision support, data analysis and visualization, computer systems architecture, quantum computing, neuromorphic computing, human-technology connections, and others.
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Degree: Bachelor’s or Master’s degree in a relevant discipline (e.g., Computer Science, Engineering, Information Systems, Information Technology, Internet of Things, Quantum, Applied Math, Data Sciences, Decision Science, Machine Learning, or other technology majors.
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Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models to quickly perform segmentation and object detection tasks with limited training data using satellite imagery.
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The Arc Institute is a new scientific institution conducting curiosity-driven basic science and technology development to understand and treat complex human diseases. You are an individual with a deep understanding of computational genomics, bioinformatics, machine learning, statistics, next-generation sequencing, and single-cell multi-omics.
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Driven by a “science-to-solutions” philosophy, we provide scientific leadership and technology to enhance national security, mitigate natural hazards and optimize disaster response.
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Experience, or desire to learn, data science techniques, including data tidying, scripting in R or Python, and visualization through Excel, Python, R, JavaScript, or Tableau Experience, Google Cloud or desire to learn, web programming, including React, Svelte.
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PNNL's Earth System Science Division enables energy independence and national security through leadership in earth systems science, engineering, and decision analytics. Our interdisciplinary scientists steward a breadth of efforts that encompass research on plants to groundwater science and coastal zones, to storm prediction.
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Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them.
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learning and computer science jobs Title: technology Company: Geo Next Generation High School Indianapolis in Kekaha, Hawaii
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