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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
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Technology Core , Proteomics and Metabolomics Centers , modern plant growth facilities , agricultural experiment stations , an imaging center , and an electron microscopy core . Minimum Qualifications: Ph.D
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Differentiate iPSCs into midbrain dopaminergic neurons and organoids for phenotyping and compound testing High content imaging and automated image-analysis Analyze omics data Collaborate closely with
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in basic equipment operations and acquiring diagnostic imaging studies in a timely manner and the ability to adapt them to individual patient need based on the requested procedure and patient
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provide detailed insights into the atomic-level processes. By linking mechanistic understanding at the atomic scale to system-level performance, this project aims to establish design principles that can
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biology, structural biology, imaging or proteomics. Learn more about the Program: Download PDF Appointment Process: Appointments will be made through a competitive and transparent selection process with
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biodistribution of oligonucleotide-based modalities in mouse models. Preferred but not required: Experience with toxicity studies and in vivo imaging (e.g., IVIS, bioluminescence, fluorescence). Molecular and
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technologies in industry and facilitates technological innovation and knowledge transfer. Discipline, including, but not limited to: Electronic and Information Engineering, Computer and Data Engineering