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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research program involves the study of machine learning
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period, but with the intention to extend subject to stage-gate approval of the full programme. This is a new role which will define the roadmap, champion the vision to senior stakeholders, and lead the
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Qualifications Bachelor's degree in Allied Health, Computer Sciences or related field, and 5 years' experience in applications technology leadership, management or equivalent combination of education and
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described in our strategic vision, Pro Futuris, and academic strategic plan, Illuminate. Connections working at Baylor University More Jobs from This Employer https://main.hercjobs.org/jobs/21981876/program
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Deep Learning libraries (e.g., Pytorch, Tensorflow, Keras) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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learning systems, among others. Successful candidates will be responsible team players and passionate on cutting edge computer vision and machine learning technologies, as well as possess deep understanding
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills
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behavioural experimental design and statistical modelling; computer vision and AI techniques; explainable AI and human–machine comparison methods; and responsible innovation. The student will work closely with
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science, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time