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Expert in data collection and analysis/interpretation, measurement & analysis automation/scripting (e.g. LabVIEW, Python) as well as presentation of experimental findings, DOE, SPC. Working across multidisciplinary teams and acting as a point of contact and knowledgeable resource for crystallography, crystal growth and X-ray diffraction-specific questions and/or challenges.
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Proficient with FEMAP, NX Nastran, Matlab, Mathcad, Labview, and/or Python. Understands the intricacies of production processes including but not limited to sheet metal, composites, 3D printing, machining, waterjet and laser cutting, welding, bonding, etc.
$140,000 - $190,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with instrumentation and data collection (LabVIEW, Arduino, etc.) Experience with instrumentation and data collection (LabVIEW, Arduino, etc.) As a Thermal Engineer , you will select thermal components, develop algorithms for thermal comfort, and help prove the robustness of those components and algorithms.
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Programming experience: Python, LabVIEW, MATLAB, or C programming. The Senior Software Verification Engineer will work with software engineers, hardware engineers, and scientific staff during verification activities and mixed signal analog firmware test development.
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The Senior Software Verification Engineer will be responsible for designing, developing, troubleshooting, and debugging software programs for the company’s current and next generation SCS systems. Work closely with the Software development team to develop and implement embedded software solutions to meet product requirements and written specifications.
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At least ten (10) years relevant experience in the development of engineering software and tools for embedded control environments, including Matlab, Simulink, dSpace, LabView, HIL/SIL test environments, C.
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Familiarity with Python/LabVIEW/TestStand automation software, a plus. Element Science, Inc. is a medical device and digital health company focused on developing solutions at the intersection of clinical-grade wearables, machine learning algorithms, and lifesaving therapies in order to address leading causes of death and hospitalization in patients with heart disease, primarily as they transition from the hospital-to-home.
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