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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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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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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 will also work with scientists and with experts in data management, lab automation, molecular design, and machine learning in the Global Biologics organization to build and continuously improve data infrastructure.
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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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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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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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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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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.
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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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Analytical Skill, Analytical Skill, Analytical Thinking, Chemical Biology, Chemistry, Clinical Trials, Communication, Curiosity, Data, Data Analysis, Design of Experiments (DOE), Detail-Oriented, Drug Development, Drug Discovery Process, Ethics, Gene Therapy, Group Problem Solving, Immunology, Inventory Management, Laboratory, Large Group Presentations, Leading Project Teams, Life Science, Machine Learning (Ml), Medical Research {+ 9 more.
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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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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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machine learning data management robotic process automation jobs Title: director in Boston, MA
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