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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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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications. As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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We're looking for a medicinal chemist to drive our drug discovery projects, who is also excited about partnering with machine learning scientists and software developers to advance our computational platforms that accelerate compound design and synthesis.
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Advanced knowledge of math, statistics, multivariate analysis, statistical tests Advanced Python coding skills Experience with one or more machine learning frameworks such as TensorFlow and/or PyTorch Understanding of numerical implementations Understanding of cloud computing Knowledge of data querying knowledge of EMG, EEG, ECG, IMU, CV algorithms Experience with C.
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Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. Amazon SageMaker, Azure ML, Databricks. Support AAG leadership in extending and growing our machine learning, engineering and analytics capabilities.
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The Algorithms, Machine Learning, & Data Science Group within AES Advanced Tech Team creates advanced algorithms in the fields of machine learning, artificial intelligence, signal processing, intelligent control, and other areas of electrical engineering and computer science that are of strategic interest to the AES Business Unit’s goals and roadmaps.
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
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We are currently sourcing for a Lead Software Engineer, Machine Learning to work at Fidelity Investments. As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines.
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Drive cross-functional collaboration across our data science, machine learning, lab informatics, and medicinal chemistry teams to advance our computational infrastructure for our drug discovery and development mission.
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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 LINC project brings together a multi-disciplinary group of experts from 8 institutions (Brigham and Women’s Hospital, Columbia University, Harvard University, Massachusetts General Hospital, Massachusetts Institute of Technology, University College London, University of Rochester, Weill Cornell Medicine) to develop novel imaging technologies and combine them with machine learning to produce detailed wiring diagrams of the brain.
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Bachelor's, Masters, or PhD degree preferred in Machine Learning, Robotics, Computer Science, Computer Engineering, Mechanical Engineering, Applied Mathematics, Statistics, or a related field.
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The world of healthcare is changing fast and Commonwealth Radiology Associates is the “tip of the spear” when talking about advancements in Diagnostic Modalities, Image-Guided Intervention, AI, Machine Learning, and Health Blockchain Technology.
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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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PhD or MSc in computational biophysics, computational chemistry, chemical engineering, computer science, machine learning or related field. Development and implementation of advanced data analytics and state-of-the-art machine learning models to generate insights from proteomics (ABPP) data, protein structure, and protein dynamics to enhance target prioritization and structure-based drug design efforts.
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machine learning jobs Title: electrical Company: Autodesk in Somerville, MA
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