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Have experience applying signal processing, image processing, pattern recognition, machine learning, deep learning, or related techniques with respect to signal extraction from sensors.
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As a not-for-profit university affiliated research center, APL also delivered solutions to our nation's national security challenges, as proven with the recent Deep Space Advanced Radar Concept (DARC) Tech Demo, and acts as a trusted partner with the US Space Force in space domain awareness and space-integrated warfare.
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Have 3 or more years of experience applying signal processing, pattern recognition, machine learning, deep learning, or related techniques with respect to information extraction from electromagnetic systems.
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Prepare a beautiful, orderly environment that fosters trust, exploration, deep learning, and independence. Have familiarity with child-led philosophies such as Reggio Emilia or Montessori and/or open to learning more.
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Willingness to travel up to 10% of the time as needed You'll go above and beyond our minimum requirements if you have: An MS or PhD in Engineering, Mathematics, Physics or Computer Science At least 10 years of relevant professional experience in this field Experience with advanced data fusion algorithms involving dissimilar sensors Deep experience with sensor signal and image processing algorithms and processing platforms An Active TS/SCI clearance Why work at APL.
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Our projects span multiple different data modalities and incorporate advanced algorithms, deep learning, and statistical techniques to uncover patterns in social media, structured and unstructured text, time series, geospatial, and imagery data, and must operate under challenging constraints not typically found in the commercial world.
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Experience with data science techniques and algorithms such as classification, clustering, random forests, deterministic forests (jk), hierarchical modeling, deep learning, Markov Chain Monte Carlo, and others.
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Strong understanding of Computer Science fundamentals (algorithms and data structures) as well as modern techniques in machine learning and deep learning, deep learning model architectures (C/RNN, attention/memory, autoregressive, etc.
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STR is committed to creating a collaborative learning environment that supports deep technical understanding and recognizes the contributions and achievements of all team members. Experienced researcher and team member who is excited to work with mission partners to leverage cutting-edge data science and machine learning research for immediate impact.
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Keywords: data mining, statistical analysis, Gaussian, Markov Models, Hierarchical Clustering, K-Means, Linear Regression, Logistic Regression, Monte Carlo Simulation, Neural Networks, deep learning, AI, algorithms, general linear model, GLM, random forest, gradient boosted models, neural networks, optimization, data visualization, Google Cloud Platform, GCP.
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Have 4+ years of experience in designing and implementing algorithms involving one or more of the following: classification, clustering, deep learning, decision making, AI explainability, stochastic processes, detection and estimation theory, information theory, Bayesian inference of time varying systems, tracking and data fusion (e.g., KF, MHT, IMM, etc.
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Utilize deep learning principles and architectures, including CNNs, RNNs, and transformers, apply these techniques to natural language processing tasks. Document predictive models/machine learning results that can be incorporated into client-deliverable documentation.
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M.S. or PhD in a scientific field and 5+ years of relevant experience after Bachelor's degree (work or post-graduate) While this position is ideally suited for a senior data scientist or machine learning researcher, individuals who feel they meet most of the requirements are encouraged to apply to work with our team leaders and have meaningful impact on our nation's safety and security.
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Oversee the continued development of machine learning including supervised machine learning, unsupervised machine learning, deep learning, optimization solutions, image/visual analytics, and natural language processing.
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3+ years of experience leveraging analytics to measure marketing effectiveness with a focus on measurement and attribution Machine learning based attribution or television attribution preferred Experience working with and measuring TV, digital media, and CRM data Deep knowledge of statistics/data science, including regression, hierarchical or mixed regression, and machine learning techniques (Naïve Bayes, Markov Chain, Random Forest etc.
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deep learning jobs in Fulton, MD
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