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Topics of specific interest include: (i) decision making under uncertainty / optimal design and control of experiments and physical or biological systems; (ii) uncertainty quantification for physical or biological systems or machine learning; (iii) optimization; (iv) model reduction / digital twins / surrogate modeling or emulation; (v) modeling & simulation; (vi) scientific machine learning; (vii) computational and experimental workflows and pipelines for science and engineering problems.
$70,200 - $116,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience in statistical learning methods for GTM attribution and building from the ground up end-to-end data driven attribution systems which may include marketing mix models (MMM) and algorithmic multi-touch attribution (MTA.
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Direct supervisory relationship with the Dean, Liberal Arts and Social Sciences; Dean, Mathematics and Natural Sciences; Dean, Allied Health and Emergency Services: Dean, Learning Resources, Library and Assessment; Dean, Adult Education and Literacy, Dean, Career and Technical Education; Executive Director, Workforce Development and Community Education; Executive Assistant and Coordinator, Academic Affairs.
$111,994 - $190,389 a yearExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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The Department of Homeland Security (DHS) is recruiting professionals to support a range of developmental roles in Cybersecurity Data Science, including Data Scientist, Artificial Intelligence (AI) Specialist, AI Operationalization Analyst, Data Modeler, Data Security Analyst and Operations Research Analyst.
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Apply knowledge of statistics and mathematical theory to develop and integrate new and emerging technologies, such as machine learning and deep learning concepts and techniques. Analyzing and defining data requirements and specifications using various tools and methodologies (e.g., Statistical Package for Social Sciences [SPSS], Statistical Analysis System [SAS], R Analytics, Statistics and Data [STATA]) to discover new patterns and behaviors providing DHS Headquarters (HQ) and/or Component stakeholders actionable recommendations.
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Using various tools (e.g., SPSS, SAS, R, STATA) and methodologies for analyzing and interpreting complex data to discover new patterns and behaviors and provide usable information to decision makers and other users.
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A minimum of 8+ years of related experience in data engineering, machine learning, AI, data science, and technical leadership. Establish technical standards, best practices, and methodologies for data science, machine learning, and artificial intelligence projects.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Director, AI Data Scientist / Machine Learning Engineer. You will be a significant contributor to our efforts to develop, validate, and implement cutting-edge machine learning algorithms, including the use of Large Language Models (LLM), applied to diverse healthcare data sources (e.g. electronic medical records.
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We are looking for a candidate with experience as a data scientist for machine learning and natural language processing problems. To make this vast amount of information more accessible, we have built a variety of tools including a search engine, a machine-learning-driven search intent classifier, an LLM-driven question -answering system and an ontology/ taxonomy all supported by reference data about companies, industries, and our analysts.
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Surgical Data Science Collective(SDSC) is non-profit organization aiming to reduce those numbers by using the latest advances in computer vision and machine learning to analyze surgical videos, after surgeries have been conducted.
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Research and develop state-of-the-art model compression techniques including QAT, model distillation, pruning, quantization, model binarization, and others for deep learning models. Hands-on experience in computer vision and deep learning frameworks, e.g., OpenCV, Tensorflow, Keras, Pytorch, and Caffe.
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Additionally, we are dedicated to crafting exceptional data infrastructure and innovative solutions in the realms of data science and machine learning. Stay up-to-date with the latest advancements and trends in machine learning and data science and apply them to evolve the measurement system.
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You will identify and address an applied machine learning problem in the enterprise co-pilot system, working with ML Engineers across the organization to adopt and productionize LLM usage. Passionate about natural language understanding, information retrieval, or machine learning.
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Using Databricks, which was named to both the Magic Quadrant for Cloud Database Management Systems and the Magic Quadrant for Data Science and Machine Learning Platforms, you'll using best in class technology to help our customer solve some of their most challenging data problems.
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learning job Title: sr data scientist Company: Verizon
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