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Supervise the development and deployment of Robotic Process Automation (RPA) and PowerApp solutions to digitally enhance operational efficiency. data storage, database infrastructure, and data engineering) to maintain efficient and secure management of data assets as well as application hosting.
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You are familiar with applied data science methods, feature engineering and machine learning algorithms. We are currently sourcing for a Lead Software Engineer, Machine Learning to work at Fidelity Investments.
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Should have a strong background in at least two of the following areas: Algorithm Development, Machine Learning/AI and Data Analysis, Mathematical Modeling and Simulation, Digital Signal Processing, Control Algorithms Design.
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IT-infrastructure, data security and project management tools (AWS, Dynatrace, CyberArk, Azure DevOps, Confluence, Jira, etc.) Concepts of process automation and digitization (e.g. RPA.
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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.
$120,000 - $160,000 a yearExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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This involves the development of a control system architecture, selecting the components to be used, detailing schematic diagrams and system documentation, programming controllers (PLC, DCS, RTU), programming the process visualization (HMI/SCADA), developing databases for archiving/displaying historical system data and implementing/commissioning the control system at the client’s facility.
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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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Experience with any of the following Frameworks: Spring, Django, R Shiny, Tensorflow, MXNet Understanding or Application of Machine Learning and / or Deep Learning Experience in a scientific environment.
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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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Through this opportunity, you will work with a multi-disciplinary team consisting of engineers, scientists, and clinicians to process large biomedical datasets, develop and evaluate machine learning algorithms, and implement data visualization tools for advanced medical imaging technologies.
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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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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Coordinate with data management study leads, clinical operations, internal stakeholders and external vendors to map non-EDC data from collection through analysis.
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To do this, you must interface directly with machine shops, sheet metal fabrication shops, internal staff members and management, as well as customers. Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities.
$150Full-timeExpandApply NowActive JobUpdated 27 days ago - UpvoteDownvoteShare Job
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As a Machine Learning Engineer, you will play a critical role in the development, deployment, and optimization of machine learning models with a strong emphasis on large language models (LLMs) and MLOps.
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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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machine learning data management robotic process automation jobs in Cambridge, MA
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