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We are recruiting highly ambitious and motivated Postdoctoral Researchers in the Division of Biomedical Informatics (BMI) within the Department of Health Outcomes and Biomedical Informatics (HOBI) at University of Florida (UF) with a focus on various aspects of data science, especially Artificial Intelligence and Machine Learning (AI/ML.
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The URBS-lab focuses on the development and application of machine learning, artificial intelligence, and statistical methodologies targeting a variety of domains and data types within biomedical research.
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AI & Computational Sciences, Novartis Biomedical Research Leadership Role in Chemistry-based AI/Machine Learning. The AI & Computational Science (AICS) team at Novartis Biomedical Research is dedicated to revolutionizing drug discovery through AI. Our mission is to accelerate the development of transformative medicines for patients worldwide.
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PhD, MS or BS in computer science, electrical engineering, biomedical engineering, bioinformatics, computational biology, physics, mathematics or equivalent. and machine learning and deep learning frameworks (e.g. TensorFlow, Keras, PyTorch.
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Ideal candidates will have a minimum of a Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
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Requires a PhD in related field or equivalent industry experience in related field such as Bioinformatics/Biomedical Engineering/Data Science/Computer Science/Statistics/Applied Math or related majors.
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Broad science and technology knowledge base that includes statistical and finite element modeling, clustering and classification, signal processing, and Machine Learning. Position Preferences in health physics, biomedical engineering, applied mathematics, biological mathematics, or a related discipline.
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Education Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.
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Duties & Responsibilities: Instructors for Computer Science will provide students with a curriculum that encompasses a wide range of relevant topics, such as knowledge-based artificial intelligence, principles of machine learning, and interdisciplinary applications across fields such as biology, biomedical engineering, and finance.
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Required License / Registration / Certification Physical Requirements Ability to communicate Area of Specialty Data Analytics, Machine Learning, Data Visualization, Big Data, Data Mining, Data Engineering, Information Retrieval, Artificial Intelligence, Data and Information Quality, Data and Information Security and Privacy, Biomedical Informatics.
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Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc. A minimum of 2 years of industry or research experience in signal processing and/or machine learning.
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AI & Computational Science (AICS) is seeking a highly motivated and experienced incoming senior expert in the domain of AI/Machine Learning applied to the Life Sciences to push the frontier of disease biology understanding and drug discovery.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Applicants should have completed a Ph. D. or is nearing completion of a Ph. D. in bioengineering, biomedical engineering, biophysics, machine learning, electrical engineering, neuroscience, neurobiology, optics, molecular or cell biology, or related fields with a strong experimental background, academic history, and publication record.
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A recent or almost completed Ph. D. degree or equivalent experience in a quantitative field (e.g., biostatistics, epidemiology, artificial intelligence, computer science, operations research, statistics, industrial & systems engineering, applied mathematics, health economics, biomedical informatics, or similar.
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