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Design, develop, and implement machine learning models and algorithms from sensor, facility, and operations real-time data to optimize and improve the functionality of decisions addressing waste reduction, production optimization, predictive maintenance, and environmental impact.
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An advanced degree (master’s or doctoral) in a quantitative field, including but not limited to Computational Biology, Computer Science, Data Science, Applied Mathematics/Statistics, all relevant engineering and science disciplines.
$144,000 - $216,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls.
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We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology.
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Contribute to the further enhancement of the data science platform and infrastructure jointly with the data engineering team. Matchpoint Therapeutics is looking for an exceptional scientist who can develop and integrate cutting-edge data science solutions in collaboration with other scientists and engineers.
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The Emulation Tooling and Modeling Software Engineer will also support model development for sensors, actuators, dynamics and environmental factors from first principles, measured data, available documentation/literature and hardware/software artifacts.
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Expertise in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem. PhD in computer science, applied mathematics, physics, computational biology or other quantitative disciplines.
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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 clients facility.
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As a Lead Machine Learning Engineer on the National Grid Data Science team, you will develop data pipelines, take data science prototype models to production, fix production bugs, monitor operations and provision the necessary infrastructure in Azure.
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Desired fields include acoustic sensing, acoustic communications, unmanned underwater vehicles, maritime autonomy, oceanography, and climate science to support missions ranging from maritime defense to sustainable development of the Blue Economy.
$120,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise in protein design and bioinformatics, including molecular modeling (homology modeling and molecular dynamics simulations) using in silico tools such as MOE, Maestro, NAMD, Schroedinger or VMD, etc.
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LASE Innovation is a life science platform startup company that is ushering in a new era of ultrahigh dimensional single-cell analysis to solve complex biological problems and diseases by providing access to high-dimensional single-cell data to every laboratory.
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Experience with Statistical analysis tools in Python and R as well as data science app development (R shiny/Streamlit). Knowledge of best practices in software engineering for reproducibility and data management skillsAbility to work in and adapt to a fast-paced environment Preferred Qualifications: Experience with protein co-evolution analysisExperience with NGS and bioinformatics toolsExperience with agile methodologies.
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The Davies Lab have used unoccupied aerial vehicles to collect a large amount of LiDAR data spanning natural and experimental gradients of climate, wildlife abundance, fire frequency, and other factors at multiple sites across Africa, which will be available for use by the postdoctoral researcher to answer questions related to animal and landscape ecology.
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Strong understanding of scientific sampling methodologies and the state-of-science on a broad range of terrestrial, wildlife, soil, and water quality issues. Ph. D. in Water Resources, Environmental Science, Ecology, Environmental Engineering, or another related field.
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data science predictive modeling jobs Company: Harnham in Lexington, MA
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