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Build and lead the data science team translating small molecule and proteomic drug discovery challenges into breakthroughs via deep learning applied to computational chemistry. This position is ideal for someone with deep expertise in machine learning, deep learning (particularly for building biologically meaningful representations of chemical structures), and computational chemistry, sciences and who is committed to building a high-preforming team.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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Engage in planning sessions in collaboration with other Educator-Advisors and STEAM technician/makerspace manager to prepare for learning experiences and reflect on learning (to inform lessons and curriculum planning.
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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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The Senior Lead Data will be responsible for partnering with Technology, Machine Learning, Product Architecture, and other Capital One teams to support the development of the Finance Tech Data Strategy into products and services we create and consume.
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Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities. Ability to spin up quickly on topics in Precision Medicine, Next Generation Genomic Sequencing, wet lab workflows, and Bioinformatics.
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7+ years experience architecting and developing AI or machine learning solutions on platforms such as AWS, Databricks, Azure, Google Cloud and OpenAI. Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks.
$140,000 - $307,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Rope access experience or an interest in learning rope access techniques (SPRAT, IRATA). Actively engages multiple perspectives when solving problems, seeks to learn from peers, and encourages reciprocal learning among team members.
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It leverages technologies like robotic process automation (RPA), machine learning, natural language processing, and blockchain to help its clients enhance operational efficiency, improve customer experience, and drive business growth.
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As a Machine Learning Engineer II with CodaMetrix you will help with translating proof-of-concept ideas to product grade solutions. The Machine Learning Engineer II reports to the Director of Architecture.
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We have a fast-growing team that's distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
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We are looking for a passionate senior machine learning engineer to join the team to partner with us to extend our existing set of traditional ML technologies and infrastructure and to help us blaze a path in the generative AI space.
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Ensure that respect for diversity, equity, and inclusion, social-emotional learning, and academic excellence are emphasized as core values of the School. We welcome candidates who will add to the diversity of our community and who have demonstrated a commitment to diversity, equity, and inclusion in their teaching and learning.
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The Youth Workplace learning Coordinator will be a member of the city’s Youth Services Team, a newly established division within the Health and Human Services Department that promotes and fosters the development of resilient, prepared, and engaged Somerville teens.
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The purpose of the is study is the Integration of machine learning and genomics to predict outcomes for newly diagnosed, relapsed and refractory mature T-cell and NK-cell neoplasms: a global study of the PETAL Consortium.
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learning job Title: learning architect Company: Microsoft Corporation in Boston, MA
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