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Drive both short term and long-term research initiatives in areas such as artificial intelligence, machine learning & data mining, natural language processing, big data systems, information and data visualization, social & cognitive science.
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Carrying out preprocessing of structured and unstructured data and detecting trends, patterns in data sets and improving data models with advanced analytics and deep learning capabilityEnhancing data collection procedures to include all relevant information for developing analytic systemsDeveloping prediction systems and machine learning algorithmsWhat you’ll bringMin. of 5+ years of professional work experience in data science and machine learning.
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Teaching responsibilities for this position are envisioned to include undergraduate and graduate level courses offered by the department and related to the successful candidate's discipline and background, including computer applications, and potential electives on topics of big data analytics, circular economy, machine learning in agriculture, agro-bioinformatics, eco-bioinformatics, and Sustainable Systems Management (SSM) program courses.
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
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Masters or Ph. D. in Machine Learning, Artificial Intelligence, Computer Science, or a closely related field, with a specific focus on natural language processing (NLP), large language models, or deep learning techniques.
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Minimum Qualifications Bachelor’s Degree in Instructional Design, Information Systems, Computer Science, Online/Distance Education, Instructional/Information Technology, or a related field.
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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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PhD in a relevant discipline such as computer science, math, computer engineering, statistics, cognitive science, electrical engineering, bioengineering, data science, etc.
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Coursework in the theory and applications of astrodynamics, remote sensing, spacecraft design, aerospace systems operations, computational fluid dynamics, machine learning, or complex systems integration is desired.
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The Data Science team at Meijer leads the strategy, development and integration of Machine Learning and Artificial Intelligence at Meijer. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
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Demonstrated experience and aptitude in a hydrology context with experience in: (a) remote sensing data products, (b) data analytics, data wrangling, data management, and data synthesis, (c) machine learning approaches for mapping, (d) numerical and analytical modeling environments (e.g. Python), and (e) geoprocessing and GIS analytics.
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Master's Degree Computer Science, Computer Engineering, Information Technology, Software Engineering or equivalent technical discipline and 5+ years of experience in software engineering with a strong background in DevOps and Infrastructure as Code, supporting Machine Learning and Data Science workloads preferred.
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Participate in the development of a machine learning framework that will allow for the computer driven control and analysis of VENUS. This framework will be made generalizable enough to be applied to other Department of Energy accelerator-related systems.
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Strong machine learning experience is preferred. Develop AI/ML models, knowledge graphs and NLP pipelines; incorporate computational strategies with graph-neural networks, deep learning, multimodal fusion, transformer models, transfer learning, contrastive learning as appropriate.
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Leads the team in developing challenger models and/or replicating model development through predictive modeling, machine learning, deep learning, time-series modeling/forecasting, stress testing, heuristic models, actuarial models, simulation, optimization, and/or other techniques including models that require specialized skills.
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computer science machine learning management information systems jobs Title: solutions Company: Pwc in Arlington, Texas
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