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The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. We are in search of an Electrical/Computer Engineer to help us design, analyze, test and deploy pioneering electrical and electromechanical systems.
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Master’s degree in data science, business, sciences statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field (MBA Preferred.
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7 years of related experience with a Masters' degree in Optics, Optical Engineering, Applied Physics, Computer Science, Software Engineering, Machine Learning, Systems Engineering, Mechanical Engineering, Electrical Engineering, Computer Engineering, or related degree.
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Proven publications in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields. Individuals in this role are expected to be recognized experts in areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, graphical models, reinforcement learning, computer perception, natural language processing and data representation.
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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Experience in real-time computer graphics or modern GPU programming (CUDA, OpenGL, OpenCL.
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Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering.
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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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Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics. Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
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MS, or PhD in Computer Science, Computational Mathematics, Applied Mathematics, Engineering, Data Science, Statistics or equivalent. Use of statistical models including experience with regression, classification, clustering, NLP, and computer vision.
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Ph. D. in Statistics, Applied Mathematics, Biomedical/Chemical Engineering, Computer Science, Physics, Computational Biology, or related field. Stay informed with emerging literature and science in the modeling and simulation sciences.
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Bachelor’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and five (5) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
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Bachelor’s degree preferred; Computer Science, MIS, or Engineering preferred. This role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows.
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Master’s degree in Computational Biology, Bioinformatics, Applied Mathematics, Computer Science, Electrical Engineering, or other quantitative field preferred. The ideal candidate would have a Masters or above in a quantitative field (computer science, applied mathematics, bioinformatics) as well as knowledge of modern molecular biology and genomics.
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A Master's or PhD degree in biostatistics, data science, biomedical informatics, epidemiology, public health, computer science, applied mathematics, engineering, or a related field.
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Many areas of expertise related to computer science and electrical engineering, such as AI/ML, computer vision, image processing, algorithms, digital signal processing, audio engineering, data science & analytics, distributed systems, cloud, edge & mobile computing, natural language processing, knowledge engineering and management, social network analysis, computer graphics, image & signal compression, computer networking, IoT are highly relevant to our research.
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computer science applied jobs in Melbourne, Florida
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