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The faculty in the department conducts research in areas such as cybersecurity, cyber identity, computer vision, data science, big data, artificial intelligence and machine learning, cloud computing, software engineering, multi-agent and social computing.
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Argonne’s Leadership Computing Facility (ALCF) and Mathematics and Computer Science Division (MCS) is looking for a Postdoctoral appointee working at the intersection of scientific machine learning SciML and large-scale simulation codes.
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Applicants should possess a PhD in a relevant discipline (computer science, machine learning, epidemiology, electrical engineering, or applied mathematics) and have established an excellent research profile in signal processing or machine learning.
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Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.
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A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology andor computational pathology (required.
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Adidevtechnologies.com) is a premier IT consulting firm delivering top-notch, Machine Learning Engineer, iOS and Android, data scientist, Developer solutions to industry giants including Delta, Google, Apple, Spotify, US Bank, FedEx, and more.
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3 years industrial experience in Machine Learning, Artificial Intelligence AI/ML, Deep Learning, Cloud Computing, Applications Development, Cybersecurity, IT, Computer Science, System Support, Databases/Fulfillment, Storage, Electrical Systems, Software Design/Development, Programming or Robotics required.
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Experience with IT infrastructure such as database systems, cloud computing (such as Databricks, AWS), and high-performance computing in Linux environments. Broad understanding of modern data science methods, particularly machine learning, in advancing drug discovery (e.g., predictive modeling, generative modeling, retrosynthesis prediction, active learning, explainable ML.
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Strong proficiency in Cloud computing, Microsoft Azure - Databricks, Azure IoT, Kafka and Scada systems. Partner with Data Architecture, emerging technologies and data engineering teams to enable data integration patterns to democratize real-time data for analytics developments (Machine learning, Visualization, Data analysis.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
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Qualifications: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and quantum chemistry, experience with machine learning regression methods.
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Have classroom or professional experience developing and/or implementing machine learning algorithms applied to biomedical data, including but not limited to neurophysiological data.
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Strong programming skills in Python and modern machine learning platforms are preferred; Experience with computing in cloud environments is a strong plus; some experience with high performance computing and database administration is desired but not required.
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Demonstrated aptitude and experience with: (a) assembling and synthesizing disparate remote sensing products for mapping building/infrastructure development, (b) assessing flood vulnerability, (c) artificial intelligence/machine learning techniques applied to mapping buildings and flood exposure, (d) surface water flow and flood modeling, and (e) social vulnerability metrics.
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machine learning applied mathematics cloud computing jobs Company: The University Of Texas At Austin in Anoka, Minnesota
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