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The multi-disciplinary team consists of talented technical staff with expertise in electromagnetics, optics, signal processing (communication, GPS), RF design, statistics, optimization, computer vision, machine learning, autonomous control, software engineering, and embedded systems.
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Bachelor s degree in a relevant field of study (including, but not limited to Remote Sensing, GIS, Activity Based Intelligence (ABI) Cartography, Applied Mathematics, or Geography). Have 8 years of progressive experience with operational and tactical level intelligence performing Processing Exploitation and Dissemination (PED) of remotely sensed data to include Hyper/Multi-Spectral Imagery (HSI/MSI), Thermal/Infrared Imagery, Electro Optical Imagery, Synthetic Aperture Radar (SAR), And Light Detection and Ranging (LIDAR), with general experience in the fields of targeting, collection, and sensor Phenomenology and their application towards intelligence problems.
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FM Global is seeking a Machine Learning Operations Data Engineer II to join our AI/ML team to support Machine Learning Engineering, working very closely with Data Science, Data Engineering, Subject Matter Experts and Solution Architecture teams.
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Role Overview As a Machine Learning Operations Data Engineer II you will develop platform tooling, deploy data science models to production and monitor production performance. You will support Machine Learning projects end-to-end and develop platform tooling for the Data Science team.
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Kafka, HDFS, Hive, Cloud computing, machine learning, LLMs, NLP & Web development experience is a plus. Experience with one or more MPP databases(Redshift, Bigquery, Snowflake, etc) Whether you are an individual or an institution, we help you buy, sell, and store your bitcoin and cryptocurrency.
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The ideal candidate will have a solid background in NLP, deep learning, and machine learning, with expertise in fine-tuning LLMs to solve complex language understanding and generation tasks.
$121,030 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
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Experience with implementation of modeling and simulation (either PDE-based fluid dynamics, ODE-based signaling models, or agent-based modeling) or bioinformatics / machine learning skills (project-dependent.
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Experience using existing machine learning and analytic tools such as ScikitLearn, Weka, R, and Mathematica in either applied educational or professional projects is required. At least one (1) year with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects Preferred.
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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. Spun out of Stanford in 2019, we have built an intelligent analytics platform fueled by our revolutionary device which uses machine perception and sensor fusion to provide an operations digital twin that combines factory operator activity with machine data for the first time.
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Experience using statistical analysis and computing, machine learning, deep learning, processing large data sets, data visualization, data wrangling, mathematics, and programming.
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Experience applying data preparation methods, feature creation engineering, exploratory data analysis, model creation, and data visualization applied to advanced analytics, machine learning and artificial intelligence.
$122,198 - $191,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are looking for a motivated Scientist III, Bioinformatics who has practical experience in Machine learning/deep learning (ML/DL). Help in the design and implementation of effective pipelines that use deep learning and classical machine learning on high dimensional cell culture data and multi-omics data.
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Experience applying analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory; link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the study.
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23andMe is seeking exceptional researchers with backgrounds in machine learning, statistics, physics, applied mathematics, and/or computational biology. Deep understanding of computational biology, statistical genetics, and/or machine learning.
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machine learning applied mathematics jobs Title: learning Company: Allen Institute For Ai Ai2 in Anoka, Minnesota
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