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4 PhD Fellows in Deep Learning at Visual Intelligence Research Centre and UiT Machine Learning Group
Stig Brøndbo 17th June 2025 Languages English English English Faculty of Science and Technology 4 PhD Fellows in Deep Learning at Visual Intelligence Research Centre and UiT Machine Learning Group
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and feedback. The successful applicant will work on designing and developing an architecture for modelling and simulating aggregated entity behaviours, in an event driven architecture paradigm, under
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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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, develop, and optimize new methods and techniques to address critical project or functional area needs. Participants will improve existing or develop new laboratory methods and processes, read and adapt
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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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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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analogous processes in more complex human cellular systems. The research aims to establish mechanistic understanding of molecular networks that maintain homeostasis under stress conditions. Through rigorous
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. Desired Qualifications* Experience with fluorescence imaging, electrical stimulation, computational modeling, image processing. Modes of Work Positions that are eligible for hybrid or mobile/remote work
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electrophysiology in ex-vivo mammalian retina. Record of publication in retinal research. Experience with fluorescence imaging, electrical stimulation, computational modeling, image processing. Michigan Medicine
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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