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Field
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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(this overlaps with the former themes as 2D and 3D vision is often integrated with language). Related papers by the Vision-CAIR members Theme A : Aligning Latent and Image Spaces to Connect
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/Cas9, single cell RNA-seq, cell culture with live cell imaging, immunohistochemistry with confocal microscopy, Ca2+ imaging, coimmunoprecipitation and proteomics. IUSM is committed to being
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to accelerated laboratory aging. - Conducting in-situ environmental digital image correlation (DIC) to quantify package and assembly deformation during thermal cycling - Developing FIB/TEM/SEM
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candidates] Design and develop prototype and testbed systems that will be deployed to community partners and stakeholders. All candidates will be expected to support the evaluation and assessment of deployed
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Posting Details Position Details Title Postdoctoral Fellow in Connectomics Specific Title Postdoctoral Fellow in Radiology & Imaging Sciences Appointment Type Postdoctoral Fellow Department IUSM
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. Analyze Diverse Data: Work with clinical, omics, and imaging data. Advance Therapeutic Discovery: Apply AI to identify new treatments. Develop Computational Tools: Build AI-powered neuroscience and
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molecular biology techniques: RT-PCR, western blotting, immunostaining/imaging, etc. Proficient in mammalian cell culture techniques. Independently develop protocols and establish new methodologies. Excellent
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large AI models or their applications. Current PLI projects involve work with language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and