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Institutional Review Board (IRB) submissions. Extracting retrospective data from EPIC. Manually segmenting OCT images to support AI research. The role requires frequent interaction with patients, research staff
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oncology information system, Philips Pinnacle (replacement pending), Elekta One Planning (Monaco + MIM), Epic electronic medical record system, and the Varian Velocity image registration and dose
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beam delivery to the target. These systems typically utilize PLC, VME, or MicroTCA hardware, integrated using the Experimental Physics and Industrial Control System (EPICS) framework. The architecture
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program focuses on studying complex processes under in situ and operando conditions, where energy materials are processed and characterized under realistic and industrially relevant conditions. High
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Review Board (IRB) submissions. Extracts retrospective data from EPIC; and manually segmenting OCT images to support AI research. The role requires frequent interaction with patients, research staff, and
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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engineering in healthcare. Minimum Education and/or Training: Master's degree in computer science, computer engineering, data science, information technology or related field required. PhD degree in data
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to take a leading role in studying the origin of Lambda hyperon transverse polarization in electron scattering experiments—such as the CLAS12 experiment at Jefferson Lab’s 12 GeV program and the ePIC
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recently developed in a commercial 65 nm CMOS imaging process by a large international consortium of engineers and scientists for the ALICE ITS3 upgrade and the future experiments, ePIC@EIC and ALICE3@LHC
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experience Practical experience of pulmonary MR Track record of publications in MR imaging journals as a first author Ability to help supervise PhD students and researchers in technical aspects of MRI research