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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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We have multiple openings for Postdoctoral Researchers to join our interdisciplinary team of Computational Bioengineers who will conduct research leading to our next-generation, machine learning-driven computational pipeline for protein design and optimizing protein-protein interactions as part of the Center for Predictive Bioresilience (CPB.
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You should have experience using deep learning, natural language processing, or machine learning systems. Everyday projects range from deep learning, research & development, algorithm development, natural language processing to DevOps. We want to provide access to the right tools and inspiration so you can solve complex problems creatively.
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Good knowledge of Contact Center technologies, including IVR, ACD, WFM, CRM integration, chatbots, natural language processing, RPA, and reporting/analytics. Strong knowledge of Contact Center technologies, including IVR, ACD, WFM, CRM integration, chatbots, natural language processing, RPA, and reporting/analytics.
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Knowledge in data analysis algorithms (e.g. data mining, statistics, machine learning, natural language processing, text mining, visual analytics). 4+ years of experience in Business Intelligence/data analytics tools (Tableau, Microsoft Power BI, Dashboards, etc.
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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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Demonstrated experience in cancer genomics and omics data analyses, including experience with developing pipelines for next-generation sequencing data analysis and QC. + Excellent programming skills (including R, Python, SAS) and deep-knowledge for statistical analysis and machine learning.
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With one of the largest multimedia air and land permitting and compliance teams in the country, we support client success in manufacturing and industry, liquids delivery and processing, natural gas storage and delivery, power generation and delivery, and transportation projects.
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Explore complex challenges and transform how the bank operates with Applied AI ML opportunities at Sr. Associate, Vice President, and Executive Director level in New York, Palo Alto, and Seattle, WA. As a Machine Learning Scientist, you'll apply sophisticated methods to tasks like natural language processing, speech analytics, and recommendation systems.
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Experience with solving and using machine learning for real world problems involving scientific/engineering simulations (domains/applications - industrial, life sciences, high energy physics, earth sciences – seismic, weather & climate modeling; physics types - CFD, structural, electromagnetics, optics, acoustics etc.
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Knowledge of other emerging technologies such as artificial intelligence, machine learning, or natural language processing in the context of content management. + Responsible for exploring and looking at new ways of working, using Gen AI approach for content creation, tagging, extraction, and modular content generation and support are desirable.
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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A minimum of 2 years of industry or research experience in signal processing and/or machine learning. Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights.
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Responsibilities Play a critical role in setting the direction and goals for one of our ML teams in terms of project impact, ML system design and ML excellence Be a go-to person for the most complex production performance and evaluation issues requiring an in-depth knowledge of how the machine learning system interacts with systems around it Lead and review technical designs for projects within your team, actively contributing to team-level strategies setting clear, achievable engineering goals.
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Collaborate with experts in hardware development, physics-based modeling, signal and image processing, machine learning, and embedded software engineering to develop cross-disciplinary solutions.
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machine learning natural language processing next generation jobs Company: Quantum Technologies Usa
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