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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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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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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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. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated postdoctoral fellow to develop cutting-edge methodologies in computer vision and AI to power whole slide image
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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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PRIMARY DETAIL • Salary package: $106,089 (Level A.6 - PhD) to $113,697 p.a., plus 17% employer’s superannuation and annual leave loading. • Appointment Type: Full-time, fixed Term for two years
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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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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