graduate industry experience in the development and practical application of algorithms, with experience in some of the following: Robotics, data fusion, tracking/estimation, pattern discovery & recognition, statistical inference, optimisation and machine/deep learning algorithms along with real-time implementation, and/or validation & verification. You will … methods, Multi-Object-Multi-Sensor Fusion, data-association, random finite sets, Bayesian belief networks, Dempster-Shafer theory of evidence Machine Learning for regression and patternrecognition/discovery problems e.g. Gaussian processes, latent variable methods, support vector machines, probabilistic/statistical models, neural networks, Bayesian inference, random-forests … Skills: Intelligent Systems Engineer, Intelligent Autonomous Systems Engineer, IAS Engineer, PhD, Mathematics, Algorithms, Programming, Robotics, Autonomous Decision Making, Machine Learning, Deep Learning, Data Fusion, Pattern Discovery, PatternRecognition, Computer Vision, Machine Vision, Matlab, Simulink, Stateflow, Python, PyTorch Due to the nature of work undertaken at our client more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, patternrecognition, cluster analysis, etc.) Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Strong understanding … Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, patternrecognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms., Good understanding of programming best practices, building for more »
the world safer, healthier, and more efficient through information technology, engineering and science? Are you interested making a difference by applying your Automatic Target Recognition (ATR) and Combat Identification (CID) skills toward state-of-the-art research and development problems? Leidos currently has an exciting opening for a senior … needs and then develop or recommend engineering solutions • Develop and utilize signature modeling tools and user interfaces for real world applications • Develop Automatic Target Recognition and Combat Identification (ATR/CID) solutions to classify images, discover and classify ESM data, or create efficiencies in other ATR/CID database … Synthetic Aperture Lidar (SAL) • Strong understanding of ground, surface, and air target identification principals and approaches using machine learning and/or artificial intelligence, patternrecognition and/or template matching, and other signal processing techniques • A proficiency in computational electromagnetic prediction codes such as Xpatch, SENTRi, CST more »
/ML research and development within an industry setting. Possess a strong foundational knowledge of AI, ML, and data science principles, including signal/patternrecognition, classification techniques, and deep neural network training. Have practical experience with various Data Science and ML frameworks or tools. Excellent verbal and more »
South West London, London, United Kingdom Hybrid / WFH Options
1PGR
countries, the company's document review platform offers lawyers greater insight at unmatched speeds. The software builds on ground-breaking machine learning and patternrecognition techniques developed at the University of Cambridge to read and understand legal language. The technology is used by law firms and in-house more »
South West London, London, United Kingdom Hybrid / WFH Options
1PGR
countries, the company's document review platform offers lawyers greater insight at unmatched speeds. The software builds on ground-breaking machine learning and patternrecognition techniques developed at the University of Cambridge to read and understand legal language. The technology is used by law firms and in-house more »
South West London, London, United Kingdom Hybrid / WFH Options
1PGR
countries, the company's document review platform offers lawyers greater insight at unmatched speeds. The software builds on ground-breaking machine learning and patternrecognition techniques developed at the University of Cambridge to read and understand legal language. The technology is used by law firms and in-house more »
high-value trade signals; ability to identify mispricing across asset classes Short/Medium Term Signals Ability design short term (intraday) & medium-term price patternrecognition systems based on statistical methods able capturing momentum trades PM Collaboration Work closely with portfolio managers during live implementation phases ensuring optimal more »
