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, developing, and implementing innovative machine learning models and algorithms to drive insights from the hEDS*omics multimodal dataset, encompassing clinical, environmental, and multi-omics data. This role
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of recurring processes. Respond to consulting requests requiring expertise in statistical methodologies and procedures. Provide statistical contributions to data mining operations and algorithm development
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the EarthCARE Cloud Profiling Radar (CPR) Doppler velocity observations. Lead the development of data products for convective systems for the upcoming WIVERN mission, employing a combination of forward and
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measures multi-quantum dot quantum circuits building on a successful process already developed by Salfi’s team in the QMI Nanofab facility [1]. Experimentally investigates and optimizes the performance
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Consortium (AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community
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: image processing, machine learning, and patient records. Track record of development and implementation of novel machine learning algorithms in the healthcare setting or other spaces. Extensive experience
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analytics, and software platform development for industry funded applied research projects. Teamwork with experts in innovative and novel technological solutions on industry challenges. Skills & Abilities
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across UBC. The vision for the ISC is to provide integrated services that create an enriched user experience for UBC faculty, staff and students. The Knowledge and Training Analyst develops, updates and
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 2 months ago
. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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research and development. Here, you can apply your engineering talent to develop new life-saving technologies – for example, medical imaging, wearable devices, surgical robotics and laboratory-grown tissues