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Key topics of interest include but are not limited to: natural language processing, large language models, predictive modeling for disease outcomes and personalized therapeutic recommendations, working with common data model EHR standards (e.g., OMOP), multi-modal (e.g., genomics, imaging, and clinical data) deep learning for clinical decision support, unsupervised learning to discover biologically-relevant disease subtypes, among others.
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This role demands a blend of expertise in data science and a deep understanding of the semiconductor industry, aiming to harness advanced data analytics, predictive modeling, and artificial intelligence to address complex business challenges.
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Job Highlights: Apply and develop artificial intelligence and machine learning (AI/ML) approaches (e.g. classification, clustering, machine learning, deep learning) on pharma research data sets (e.g. activity, function, ADME properties, physico-chemical properties, etc.
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Causal Machine Learning, Causal Inference, Causal Discovery, Counterfactual, Causal Deep Learning, Causal Structure, Structure Learning, Structure Equation Model, SEM, Explainable AI, XAI, Data Science, Deep Learning, R, Python, Julia, Bioinformatics, Multiomics, Integrative Analysis, Medicine, Actigraphy, Pregnancy, Precision Medicine, Personalized Medicine, EHR, Electronic Health Records.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Individuals in this role are expected to be recognized experts in areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, graphical models, reinforcement learning, computer perception, natural language processing and data representation.
$205,000 - $281,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Located in more than 30 offices and 10 creative studios around the world, its 6,000+ strong team combines strategy, technology, data science, and creative design with deep industry expertise and insights, to develop new digital solutions and business models of the future.
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Data Scientists contribute to projects involving one or more of the following disciplines: Data Science, Applied or Theoretical Machine Learning, Deep Learning, Deep Reinforcement Learning, Physics Inspired ML, Classification Systems, Natural Language Processing, Artificial Intelligence, or Computer Vision.
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Experience in data science, statistics, optimization, machine learning, and/or deep learning. Bachelor's degree in computational and engineering sciences (e.g., computer science, computational biology, electrical engineering, biomedical engineering) or other related fields.
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Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Our Data, Science & Analytics team works across our big data cloud platform and data supply chain, using advanced analytics, machine learning, AI, and deep learning methods to make an impact across our entire data ecosystem.
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Leverage data science and machine learning to develop predictive models and algorithms to enhance product experience and business decision-making. Data Science and Machine Learning.
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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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We are looking for a candidate, who is a self-starter and brings an entrepreneurial spirit, to join the Data Science and Data Analysis (DSDA) team and contribute to the data science products used to solve some of the complex issues and enhance system performance in the Battery Energy Storage System (BESS) industry that is seeing exponential growth.
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We are looking to hire a staff machine learning engineer to join our RVO Health data science team. Proven experience in data science and machine learning, preferred experience on healthcare applications and AI.
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