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Engage in continuous learning to stay abreast of the latest developments in mobile health technology, data science, and machine learning. ⢠Develop on-device data visualization and machine learning models for personalized feedback and adaptive interventions.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer. Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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Strong publication record in one or more of the following areas: computational biology/bioinformatics, biomedical informatics, deep learning/machine learning, data mining, biostatistics, or a closely related area.
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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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The Center for Targeted Machine Learning (CTML) in the School of Public Health's Division of Epidemiology and Biostatistics is an interdisciplinary hub that brings together data scientists, statisticians, computer scientists, and health professionals.
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The successful applicant will conduct analytical and experimental research in the areas of nondestructive evaluation (NDE) with an emphasis on the development of computer vision and machine learning-enhanced techniques for damage detection in wind turbine blades.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
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Experience with cloud computing platforms (e.g., AWS, Google Cloud Platform, Azure) and containerization technologies (e.g., Docker, Kubernetes) for deploying and scaling machine learning models.
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Would you like to work closely with some of the biggest names in technology Dell, Microsoft, NVIDIA and help build the data analytics, artificial intelligence (AI) and machine learning (ML) compute, storage and networking products and platforms of the future.
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The ideal applicants will have experience with one or more of the following: biophysical techniques, microbiology, synthetic biology, robotics, advanced image processing, machine learning, and magneticlaser tweezers.
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If you've used Disney+, Peacock, or other top streaming platforms, you've already benefited from Conviva's technology.
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Associate Professor - Tenure - Artificial Intelligence (AI) and Machine Learning (ML) applications to Epilepsy and Traumatic Brain Injury. Expertise is required in the specific area of of Artificial Intelligence and Machine Learning, particularly as it applies to biomedical signal processing (such as electroencephalography) and imaging analysis, including quantitative tools to analyze magnetic resonance imaging of humans with neurological disorders.
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Proficiency with Python, SQL, AWS, Unix/Linux shell, Git; Hands-on experiences in large datasets including signal, GIS, image, text or sensor data; Understanding of machine learning and deep learning methods and frameworks (Tensorflow, Keras, Pytorch, etc); Hands-on experience in designing, developing, and deploying machine learning models.
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Proven experience as an NLP Engineer, Machine Learning Engineer, or similar role, with a strong background in natural language processing and machine learning. Machine Learning and Deep Learning: Utilize machine learning frameworks (e.g., TensorFlow, PyTorch) to train and optimize NLP models.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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machine learning jobs Company: Centers Health Care in VT, Alaska
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