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imaging and spatial omics instruments. Work closely with users to understand image/data acquisition pipelines and inform computational processing accordingly. Support users in experimental design
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-edge research on spectral CT, quantitative imaging, and artificial intelligence. Position Highlights: - Research Focus: Engage in impactful research, focused on spectral CT, quantitative imaging, machine
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preclinical imaging - Proven expertise in quantitative imaging analysis and in signal or image processing - Strong analytical, organizational, and communication skills - Ability to work in interaction with
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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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in computer science, bioinformatics, physics, applied mathematics, or a related field ‒ Strong theoretical foundations and practical skills in AI and image processing ‒ Strong experience in Python and
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Qualifications PhD in Neuroscience or other related field Experience in in vivo dosing (IV,IP, SC), mouse brain stereotactic surgery, in vivo two photon imaging, image analysis Qualified applicants must be
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responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed
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or Functional ultrasound imaging or Electrophysiology (neuropixels) in behaving animals Quantitative data analysis and computational modeling of network activity Data acquisition systems, signal processing and
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research will involve Python scripting within the Thermo Fisher AutoScript environment to control operation of the microscope beam, stage, detectors, and spectrometers, with a particular emphasis on annular