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Research in Computational Data Science and Engineering includes: big data and computational statistics, AI and Machine Learning, internet of things, large and complex systems, intelligent transportation and infrastructure systems, remote sensing, autonomous vehicles, virtual and augmented reality, e-commerce, image and video processing, scientific and interactive visualization, high-performance computing, scalable algorithms, bioinformatics, and multi-scale multi-physics engineering systems.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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Must have any experience with each of the following: (1) Data Science, Artificial Intelligence, Big Data, and Machine Learning; (2) Azure Databricks, allowing for creating scalable and collaborative data analytics workflows using Apache Spark; (3) working with React JS, Angular JS, and Vue JS frameworks, including HTML and JavaScript, to develop interactive web applications; and in the following programming languages (Python, Java, C.
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Data science, machine learning, optimization models, PhD 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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Knowledge of statistics, data science, AI/machine learning, big data management. We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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Required Education: BS Computer Science, Cybersecurity, Computer Engineering or related degree; or HS Diploma and 10+ years of host or digital forensics and network forensic experience.
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Master's degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field.
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We are searching for a Computer Vision/Machine Learning Engineer to join our collaborative group that includes a mix of big data, API, and full stack development teams. BASIC QUALIFICATIONS Bachelor’s Degree required from an accredited, not for profit university or college, with degree preferably in Computer Science, Data Science, Statistics, Machine Learning, or Mathematics.
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Master's Degree MA/MS degree in Healthcare, Engineering, Mathematics, Statistics, Epidemiology, Business, Data Science, Computer Science, or related field. 6 years An equivalent of 6 years experience with big data, database query and analysis languages (e.g. Python, SQL, Snowflake SQL, R, Scala, SAS, Azure DataBricks) and data visualization tools (e.g. Power BI, Tableau) required.
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Degree in Mathematics/ Statistics/ Computer Science or a related engineering/ technical or quantitative field. Explore more AI, ML, Data Science career opportunities. Min 4 years of experience as a Data Scientist in the ad-tech industry, including the following experience in: business intelligence, data mining, analytics, and statistical modeling disciplines.
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The laboratory focuses on using big data approaches to neuroimaging and genetics, using behavioral and non-invasive MRIs to examine brain-behavior relationships after stroke. More information about the NPNL can be found at The ideal candidate should have, or will soon have, a bachelor’s or master’s degree in Neuroscience, Computer Science, Biomedical Engineering, or a related field.
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Bachelor’s degree in Computer Science, Electronic Engineering, Electrical Engineering, Information Systems Technology, or a related field and 5 years of progressive, post baccalaureate experience as Engineer III, Data Engineering or related occupation in the Big Data software development engineering.
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PhD in computer science, data science, geospatial science/engineering, remote sensing, or related discipline. One of the goals of Digital Agriculture Research Lab at Texas A&M AgriLife Research center at Corpus Christi is to develop and apply emerging technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems.
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Option 3: Master's degree in Computer Science and 4 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field. Option 1: Bachelor's degree in Computer Science or related field and 6 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field.
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