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Publications or blog posts displaying excellent writing on data science or machine learning topics. You will collaborate with company advisors from MIT and Harvard whose expertise span machine learning, medical imaging, and getting products successfully through FDA. We are looking for an individual with an exceptional Machine Learning background and track record of proven delivery who is not shy to take on extensive responsibilities.
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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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Solid understanding of machine learning methods, ideally deep learning, with experience using at least one of the following frameworks: Pytorch, TensorFlow, JAX. The Karczewski Laboratory in the Center for Genomic Medicine (CGM) and Analytic and Translational Genetics Unit (ATGU) at Massachusetts General Hospital (MGH) and the Broad Institute of Harvard and MIT is seeking exceptional computational biology candidates to build tools necessary to visualize and interpret massive data sets of human genetic variation and functional genomic information.
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They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.
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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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There are various disciplines involved in Enterprise Data & Analytics, including: data source identification and analysis, data engineering, data visualization & data science/machine learning.
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Keywords:Boston MA Jobs, Software Manager, UI, User Interface, JavaScript, React, Redux, HTML, CSS, Bootstrap, Java, PHP, Python, AWS, PaaS, SaaS, IaaS, AppSync, Lambda, Cognito, BeanStalk, CloudWatch, CloudMonitor, EC2, S3, VPC, SQL, MySQL, AWS-RDS, DynamoDB, AWS-Elastic Cache, ETL, Data Lakes, AI, Artificial Intelligence, ML, Machine Learning, Data Science, Agile, Waterfall, Work From Home, Remote, Massachusetts Recruiters, Information Technology Jobs, IT Jobs, Massachusetts Recruiting.
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Pearson VUE offers a great environment to start or grow your career, we are now hiring for a part time Test Administrator to join our team in Boston , MA. Pearson VUE is a business of Pearson, the world's leading learning company with global-reach and market-leading businesses.
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MD with clinical experience (e.g., residency), Ph. D., Masters or Bachelors degree in Medicine, Biotechnology, Statistics, Machine Learning & Artificial Intelligence, Physics, Mathematics, Computational Chemistry, Computational Biology, Biology or a related discipline.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Strong background in statistical analysis and machine learning, with knowledge of -omics data being a plus. PhD or equivalent experience in Computational Biology, Machine Learning, or related field with a focus on biology.
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Python Development: Have a minimum of 3-5 years of hands-on experience in Python development, with a particular focus on data science, machine learning, and AI. Moreover, at least 4-8 years of experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and proficiency in other Client algorithms and libraries.
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Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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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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