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Experience in applied machine learning, embedded spectrum systems, and signal processing preferred. Machine Learning | Physics | Embedded Systems | Signal Processing | Data Analysis | Nvidia | Electrical Engineering | Cloud Computing | Cuda | TensorRT | Radio Frequency | Transmission Processing | Linux OS | Pytorch | Python | Causal Inference.
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Applied AI ML opportunities are available at the VP level for our Quant AI team within the Machine Learning Center of Excellence. Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.
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Adobe Firefly Applied Science & Machine Learning (ASML) group is looking for research scientists and engineers working on generative AI models for image and video synthesis to help us build the next generation of creative tools.
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Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
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Key Responsibilities: Lead Data Science Projects: Design, develop, and implement predictive modeling projects that address critical business problems, leveraging expertise in machine learning, deep learning, natural language processing, generative AI, and other areas.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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The Risk Management & Compliance Technology Machine Learning team at JPMorgan Chase focuses on solving challenging business problems such as Anti-Money Laundering and Surveillance through data science and machine learning techniques across Risk, Compliance, Conduct and Operational Risk. Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area.
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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 new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. The Senior Director, Model Validation for Santander US Compliance models (Transaction Monitoring, Sanctions Screening, Fraud Risk, etc) will be responsible for leading the independent validation of models used by various Compliance groups in conformance with regulatory guidance on model risk SR11-07 and other regulatory requirements around Compliance models.
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Director, Model Validation for SHUSA Compliance models (Transaction Monitoring, Sanctions Screening, Fraud Risk, etc) will be responsible for leading the independent validation of models used by various Compliance groups in conformance with regulatory guidance on model risk SR- and other regulatory requirements around Compliance models.
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We are looking for a passionate Software Engineer, Big-Data Engineer, Machine-Learning Engineer, Full-stack Engineer, or UI/UX Engineer, who can contribute and make a difference in any of the different components of our Knowledge Graph Platform.
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Demonstrated track research record in the fields of statistics, machine learning, computational biology, data science or related field (computer science, physics, biostatistics, bioinformatics.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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machine learning applied jobs Title: postdoctoral in Brooklyn, NY
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