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Experience working with clinical terminology standards (e.g. SNOMED CT, LOINC and RxNorm) or in clinical Natural Language Processing (NLP) in healthcare. Providing CDI content support to Solventum HIS end user products applying Natural Language Processing (NLP) and Natural Language Understanding (NLU) in a clinical setting.
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Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
$229,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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5+ years of research experience in natural language processing, machine learning, and related fields. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence (for example, human-assisted AI, natural language processing, robotics, 3D perception, and AI platform), energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.
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Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
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Stay current with emerging technologies in natural language processing (NLP), large language models, general and generative AI, and machine learning. Knowledge of Natural Language Processing (NLP), Natural Language Understanding (NLU) techniques, Human-Computer Interaction (HCI), and Large Language Models (LLM.
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Good knowledge on Natural Language Processing (NLP). Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
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Stay abreast of the latest advancements in machine learning, natural language processing, and quantitative finance, and apply cutting-edge techniques to enhance the Trexquant’s investment capabilities.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
$232,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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We are looking for a highly skilled ML Engineer to join our R&D team, working on cutting-edge projects involving Natural Language Processing (NLP), Large Language Models (LLM), Computer Vision, Voice Synthesis, and more.
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They are seeking a highly skilled Bioinformatician with extensive experience in Large Language Models (LLMs) and Natural Language Processing (NLP) to join their cutting-edge team.
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Build production-ready models using statistical modeling, mathematical modeling, econometric modeling, machine learning algorithms, network modeling, social network modeling, natural language processing, or genetic algorithms.
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Stay at the forefront of AI advancements by continuously researching and evaluating emerging trends, tools, and methodologies in areas such as deep learning, natural language processing, computer vision, and reinforcement learning.
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They will work with NYCRD colleagues on enhanced phenotyping, including using the output of natural language processing and the GenomeDiver software to generate and have clinicians curate human phenotype ontology terms describing the patient.
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Production-level experience with core quantitative analysis techniques (e.g., predictive modeling, machine learning, artificial intelligence, or natural language processing) in a consulting environment.
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