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Familiarity with sensor fusion techniques and the integration of data from various sensors such as LiDAR, cameras, radar, and GPS. Expertise in computer vision, natural language processing, or reinforcement learning as applied to autonomous vehicles.
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A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions. A cornerstone of this roadmap is the acceleration of its data organization and adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.
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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc.
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The ideal candidate has a machine learning background, with previous experience building large-scale generative models, complex pre-processing pipelines, and comprehensive benchmarks to support scientific tasks.
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Profound experience in data science, machine learning, and data engineering programming using python and higher-level libraries such as numpy, pandas, scipy, statsmodels, scikit-learn, TensorFlow, matplotlib, Plotly, or similar.
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Strong coding skills in Python, and experience with machine-learning and deep learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, etc.) We are seeking a highly motivated machine learning/AI scientist to join our Computational Tissue Imaging Research team in the Translational Bioinformatics organization.
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The Specialized Products & Advanced Research Capabilities (SPARC) Group is seeking a Principal Machine Learning Researcher to be part of a multidisciplinary team of researchers and engineers dedicated to developing cutting-edge technologies with significant and immediate impact on our national security.
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MTSI is seeking a Network/System Administrator who will organize, install, and support government organization’s computer systems, including local area networks (LANs), wide area networks (WANs), network segments, intranets, and other data communication systems.
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Support and maintain both Rancher and OpenShift Container Platform across data centers, AWS GovCloud and closed area networks. An employer is seeking a Platform Reliability Engineer with experience in OpenShift and/or Rancher Kubernetes-based platforms to sit 100% remote for one of our largest defense customers in the Fortune 500.
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Have demonstrated experience with using machine learning methods to analyze large-scale multi-dimensional biological data (omics / multi-omics, human genetics. 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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Expert in Azure cloud computing, specializing in Azure data engineering stacks like ADF (Azure Data Factory), ADLS, Event Hubs, Snowflake, Databricks, streaming, Azure PowerShell, and Log Analytics.
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Experience with Data mining, database, functional analysis, machine learning algorithm, dashboarding and data visualization is desirable. Champion data hygiene : Drive the adoption of best practices for data quality and integrity.
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Drive the adoption of best practices for data quality and integrity. To achieve this vision, mRNA CoE is looking for data scientists who will be embedded in labs and will work closely with the scientists in the mRNA Sciences, Delivery, Chemistry, Discovery Biology and Biomarker teams.
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Past experience with Data mining, data base, functional analysis, machine learning algorithm, dashboarding and data visualization is desirable. Work hands-on with R&B Scientists & technicians in specific sites to upgrade current data operations and practices to build impactful ways of working.
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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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