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Successful candidates are expected to have experience with, or by ready to learn, data visualization; statistical methods, machine learning and AI-based methods; geospatial data management, image processing and computer vision; and text to data.
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Preferred experience applying machine learning to health/medical data (e.g., DICOM) Leverage deep learning in the context of a variety of medical data (image and text) to create solutions for image segmentation, registration, feature extraction, detection, classification, semantic understanding and inference.
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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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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
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Our verified identity platform and advanced image capture solutions are built on the latest advancements in biometric recognition, artificial intelligence, computer vision and machine learning, and trusted by.
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Research experience (publications) in the following areas is preferred machine learning, deep learning, NLP, computer vision, data mining, causal inference, information retrieval, game theory.
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Our department focuses on gathering, enriching and processing data for Machine Learning in different AI domains. Work Location: Remote in the United States Required weekly availability: about 20 hours; flexible schedule Engagement Model: Freelance/ Independent Contractor Language Needed: English (United States) Estimated Start Date: Middle of April 2024 Estimated Project Duration: 8 weeks Job Description DataForce by TransPerfect is currently looking for image annotators residing in the United States to join our team and work on one of our Image Annotation projects.
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We offer high-quality data for Human-Machine Interaction to some of the most prestigious technology companies in the world. Sourcing@transperfect.com DataForce by TransPerfect is part of the TransPerfect family of companies, the world’s largest provider of language and technology solutions for global business, with offices in more than 100 cities worldwide.
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The group leverages medical image processing, machine learning, finite element analysis, computer-aided design, virtual reality, and 3D printing to achieve these goals. Use of open-source pediatric valve image analysis applications (SlicerHeart, 3D Slicer) for interpretation of medical images.
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Experience with machine learning tasks such as natural language processing, image recognition, semantic segmentation, reinforcement learning, approaches such as Bayesian, deep convolutional and graph neural network methods, and tools such as PyTorch, Ray, TensorFlow/board, and MLflow.
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The Principal Data Scientist is a highly motivated and experienced individual proficient in advanced machine learning models, particularly language models, document understanding and analysis, and code generation.
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Research and Innovation: Staying up-to-date with the latest advancements in natural language processing (NLP) and machine learning (ML) research, exploring new techniques, and applying innovative approaches to enhance model performance and capabilities to support our clients' staffing services.
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The graduate intern will work within the computational pathology team to assist scientists on the development of machine learning approaches and refinement of existing image analysis tools.
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Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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