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- Western Norway University of Applied Sciences
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Field
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field Expertise in robotic system Familiar with ROS1 / ROS2 Good publication track record is an
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advanced techniques, including patch clamp, optogenetics, fluorescence imaging, auditory brainstem response (ABR), stereotaxic surgery, RNA-seq, and computational modeling. Key Responsibilities: Assist
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research, or regenerative medicine, ● Experience with cellular and molecular techniques, including cell culture, omics approaches, and imaging methods, ● Proficiency in data analysis, statistical methods
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. Our team is closely linked to the Magnetic Resonance and Precision Imaging community at the Nottingham NIHR Biomedical Research Centre. Applicants must be highly motivated and self-driven, with a PhD or
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techniques, image analysis, genetic manipulations, biophysical approaches, and collaborate with theoreticians to address these questions. The specific details and aims of the project will be driven by
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the supervisor(s) will help with this procedure. The candidate must be enrolled as a PhD student within 3 months from the start of the employment. Western Norway University of Applied Sciences is
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. This post is for one year initially, with possibility of extension. Research Fellows - Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be
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real world applications. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/274371/phd-research-fellow-in-deep-learning-on-image-data-for-subsurface-imaging Where
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synchrotron instrumentation, neurobiology, and computational imaging Your profile PhD degree in physics, biology, medical imaging, or a related field We encourage applications from researchers with experience