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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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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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Strong familiarity with topics of protein and macromolecular structures and interactions with other proteinsExperience with cloud environments such as AWSExperience in developing machine learning platforms using modern ML frameworks for deep learning (, tensorflow, keras, MXNet) & deploying in services such as Amazon Sagemaker.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Bachelor's degree in Computer Science, Applied Mathematics/ Data Sciences/ Data Analytics or related discipline required, advanced degree preferred.
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As a member of our Machine Learning Research team, you will design new approaches to derive insights from Pfizer’s proprietary data and external datasets to generate testable hypotheses across the drug discovery continuum with a focus on extracting biological knowledge.
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Work with Data Operation team to plan and document computer data file structure as well as to develop, program, manage, and maintain complex statistical databasesYou will need to have:PhD (or equivalent degree) in statistics, biostatistics, data science, computational biology, bioinformatics or related discipline with a minimum of 3 years relevant work experience, or Masters with a minimum of 6 years relevant work experience.
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Use computer vision and machine learning techniques to analyze video data collected in Neurobooth. Massachusetts General Hospital (MGH) Department of Neurology and Harvard Medical School (HMS) is seeking a signal processing and machine learning post-doctoral fellow for a full-time position in the Gupta Lab. The fellow will be applying diverse methodologies to uncover information in multimodal data collected from individuals with common and rare neurodegenerative diseases.
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As a leading HealthTech company based in Boston, our client develops innovative tools for programming living cells, combining mammalian synthetic biology, computer-aided design, and machine learning to improve the creation and production of biologics and gene therapies.
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Strong computer skills and a working knowledge of statistical software (SPSS/PASW, excel), BPS Databases (ASPEN/SIS, SEIMS, Data Warehouse, BIMAS, etc.) Knowledge of adult learning theory and social & emotional learning competencies.
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The Lead QA Analyst is responsible for testing BI Data solutions and enterprise semantic model, while coordinating the development of these requirements with the Data engineering team.
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Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights. Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc.
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Bachelor's degree from an accredited college or university in Computer and Information Science, Computer Engineering, Computer Systems Analysis, Information Cybersecurity and five (5) years of progressive information security experience across various information security/information technology risk management domains such as but not limited to application security, infrastructure security, identity, and access management, vulnerability and cyber threat management, security architecture, etc.
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Engineering Mechanics and Infrastructure (EMI) applies engineering mechanics, materials science, numerical simulation, innovative technologies, and collective expertise to solve our clients' toughest problems in an inspiring work environment that nurtures life-long learning and growth.
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Advanced degree in a related field such as Computer Science, Engineering, Mathematics or Quantitative Finance is preferred. Strategic Advisers is looking for a Sr. Quantitative Portfolio Analyst to join our Quantitative Model Management group within our Portfolio Engineering organization.
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PhD or equivalent in Statistics, Bioinformatics, Data Science, Epidemiology, Computer Science, Computer Engineering, or similar field. Advanced knowledge of analytic approaches including data wrangling, visualization, and machine learning preferred.
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machine learning data engineering computer jobs Title: analyst in Boston, MA
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