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The University of Southern California's Leonard D. Schaeffer Center for Health Policy and Economics is now accepting applications for one or more Postdoctoral Fellowships in health policy, health economics, and health services research with a specific focus on machine learning and data science applications in health economics and outcomes research (HEOR) and pharmacovigilance.
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Preferred Qualifications: Prior experience in ad platform, auction systems, or dual-sided marketplace 2+ years of experience as a developer, data scientist or machine learning engineer Hands-on experience with cloud technologies and service oriented architectures Track record of using data analytics for improving SW operations and organizational efficiency Advanced degree in an analytical field.
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Proficiency with image processing, machine learning, and deep learning techniques. Create machine learning-based pipelines to identify changes in spatial omics patterns of gene and protein expression in tumor tissues.
$80,196 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communication of scientific findings via peer-reviewed publications and scientific conferences.
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You will provide a range of qualitative and quantitative consulting services in the areas of data science, AI, model development, model validation, model risk management, modeling technology, model governance / controls / documentation, and financial instrument valuation.
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5+ years of experience with data engineering/modeling, consulting/training skills, information security, data governance, architecture strategy development, and executive communication.
$315,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Image processing, machine vision, signal processing and artificial intelligence, etc. and have a deep understanding of image characteristics and machine learning. related image processing libraries (such as OpenCV, lTK, etc.
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About the roleIn the role of Senior Research Developer, (internally titles: Machine Learning Engineer), you will report to the director of data science and machine learning in the Center for Data and Insights.
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Technical knowledge of neuroimaging and brain anatomy, experience with organizing, maintaining, and analyzing large brain imaging datasets, programming expertise with python, Bash and parallel computing, experience with Brain Imaging Data Standards (BIDS) and MRI—based neuroimaging software programs (e.g., FreeSurfer, ITKSna) and statistics/machine learning strongly preferred.
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A team of experts in social-emotional learning, physical activity, the education landscape, and ed-tech platforms guides us. Motivate TK/K-6th grade students through social-emotional learning and enrichment activities such as STEAM.
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Ensure accuracy and completeness of data used in QRM. Perform backtesting and sensitivity analysis of modeling assumptions. This role will be responsible for providing support for the IRRBB measurement, monitoring, and management across several RBC CUSO entities calculating and analyzing monthly EVE/NII/KRD metrics, setting up and maintaining QRM model, developing and documenting modeling assumptions, NII backtesting and sensitivity testing of modeling assumptions.
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Finite Element Model development, refinement, validation, and correlation to tests Rigid and flexible body dynamics Modeling, simulation, and verification of spacecraft launch, docking, and landing events Acceleration, shock, and vibration measurement and data interpretation of ground and flight tests General loads development for spacecraft and related ground systems Support configuration development and trade studies.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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Qualifications 3+ years of experience in data engineering, demonstrating a foundational understanding of data modeling, ETL/ELT principles, and data warehousing. Experience with data management fundamentals, data storage principles, and cloud-based data warehouses such as cloud Storage (AWS S3, GCP Cloud Storage, Azure Blob Storage), GCP BigQuery, Snowflake, or similar platforms.
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Experience must include two (2) years of experience in data mining and development of ETL processes; distributed data architectures and big data processing technologies such as Spark, EMR, Hadoop and Hive; and Realtime Frameworks, collection, and processing Realtime data using kinesis Data Streams, KCL, KDA and Firehoses.
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modeling machine learning data processing jobs in Los Angeles, CA
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