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technology for CO2 storage, capturing dissolution processes and convective mixing, validated against high-resolution complex meter-scale laboratory experiments in the FluidFlower . The project is an
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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-The-Shelf (COTS), all-digital radar systems linked to an array of ultra-stable, ultra-low phase noise oscillators. The project is part of the UK Quantum Technology Hub in Sensing, Imaging and Timing (QuSIT
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synaptic and cellular studies using patch-clamp electrophysiology, large-scale population recordings using 2-photon Ca2+ imaging in awake behaving mice, and advanced modeling + machine learning analyses
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plasticity. We study questions at a variety of levels, Ranging from synaptic and cellular studies using patch-clamp electrophysiology, large-scale population recordings using 2-photon Ca2+ imaging in awake
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lab investigates how neural circuits process visual information and drive behaviour, as well as the evolutionary development of these visual systems. By studying a myriad of vertebrate species, we aim
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, communications, science and technology. Our students are at the heart of everything that we do, and we are committed to supporting them to pursue their career and personal ambitions. Our research is engaged
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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, clinicians and imaging experts from UBC, BCCRI, and our international institutional and industry partners. The fellow will work within our multidisciplinary team (medical physicists, engineers, nuclear
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. Prior experience in at least one of the following is a requirement: physiologically based pharmacokinetic (PBPK) modeling, computational oncology/biology, kinetic modeling, advanced image processing