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Sr. AWS Cloud Engineer w/ Machine Learning Ops. You are familiar with applied data science methods, feature engineering and machine learning algorithms. Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.
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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. 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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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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The Senior Machine Learning Engineer will serve as a key technical leader, driving the design, development, and deployment of advanced machine learning applications.
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We are looking for a rock star to join our team as a Machine Learning Engineer focused on protein design. To be effective in this role, you will need to be exceptional in structural biology, biophysics, and machine learning engineering.
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We are growing a team of people from multiple disciplines who love solving complex problems with data and are excited by the prospect of creating the brains behind Iris. As a Machine Learning Engineer, you will be responsible for building the infrastructure and implementing the algorithms that make Iris smart.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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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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Using advanced machine learning and state-of-the-art non-invasive robotics, the team aims to communicate with these majestic creatures. Our core tenets are educating broad-minded students; interdisciplinary research; integration across disciplines; and balancing theory, experimentation and practice to create an unmatched environment for learning and exploration.
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You will develop novel bioinformatics and machine learning solutions and apply them to next-generation sequencing (NGS) data to discover and characterize biotherapeutics. We are seeking a collaborative bioinformatics and machine learning scientist to join the Computational Design and Predictive Modeling team in Cambridge, MA.
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Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology. Ph. D. degree in Computer Science, Machine Learning or a related field.
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Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep. Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny.
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Architect and engineer machine learning models and algorithms to identify potential drug candidates, with a specific focus on DNencoded library (DEL) machine learning.
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The Bioinformatics Scientist is responsible for analyzing antibody selection data from yeast display, implementing machine learning algorithms to enhance data analysis and lead selection, and managing the data pipeline from raw file processing to database storage.
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machine learning jobs Title: devops engineer in Boston, MA
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