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Expected Start Date: July – Sep 2025 Basic Qualifications A PhD in Bioengineering, Biomedical Engineering, Electrical Engineering, Mechanical Engineering, and/or Neuroscience Extensive experience with
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. Applicants should not feel obliged to focus on a traditionally identified paradigm. The ideal candidate for this Research Fellowship will have a strong background in a relevant area of work and be completing
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strongly encouraged. Applicants should not feel obliged to focus on a traditionally identified paradigm. The ideal candidate for this Research Fellowship will have a strong background in a relevant area of
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that come in touch with human skin can serve as vehicles for transport of diseases and their spread throughout human communities. This infection process can be mitigated by surfaces on which microbes cannot
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horizontal convection, with a particular emphasis on their application to subsurface oceans of icy moons. The UKRI-funded FLF project aims to advance our understanding of fluid dynamics processes within gas
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pipelines. Your primary focus (80% of your time) will be on leading spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical
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create a collaborative and engaged user community. A special focus lies on the operation of the multiphoton and FLIM microscopy systems and establish intravital imaging pipeline. Main Duties and
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. Set up and analyze experiments and datasets under different conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in a form of
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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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We seek to recruit a Research Associate/Fellow to join our team developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph