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Field
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filtration, chromatography for separations of complex lignin-derived streams (simulated moving bed chromatography and counter-current chromatography), and recovery of pulping chemicals. We encourage candidates
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-of-the-art MRI scanners (including one new 7T scanner) as well as MEG (Elekta Neuromag TRIUX 306-channel system). If you are at the end of your PhD and expect to defend your thesis within 6 months (and may not
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
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ABIF can be found at: http://www.mcgill.ca/abif. Primary Responsibilities 1. Technical Development & Innovation Lead and document quality control (QC) workflows for ABIF imaging systems, including
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and collaborate effectively. Experience in healthcare and medical device environments is highly valued. ● PhD in computer science, electrical engineering, biomedical engineering, cybersecurity
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self-direction and the ability to work effectively with other team members, undergraduate, graduate, and other post-doctoral researchers in the in lab. Candidates must have obtained their PhD in a
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robotic arms and performing software and hardware integration Mentor and Advise PhD thesis within the research group. Current topics include, reinforcement learning for tactile-aware manipulation skills
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perturbation modelling. The ideal applicant brings not only strong technical skills, but also interdisciplinary knowledge on the subject. More precisely: PhD degree in computer science, machine learning