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Research Associate, Translational Research Fellow - Dept. Ophthalmology Visual & Anatomical Sciences
State is a premier, public, urban research university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment
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reproducibility, Knowledge of deep-learning methods, At least one first author manuscript in the context of omics data analysis in an international peer-reviewed journal in good track for publication (to be
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School: Harvard Medical School Position Description: The Department of Health Care Policy at Harvard Medical School seeks an experienced postdoctoral fellow with a specialty in health services research
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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. Research will focus on neural data integration, neural circuit modeling, biologically grounded representation learning, and foundation models for neurobiology. The Postdoctoral Fellow will work closely with
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cross encoder architectures and retrieval augmented generation. Strong programming skills in Python and deep learning frameworks, familiarity with MLOps practices, data governance for sensitive health
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Information , Data Visualization , Deep Learning , High dimensional Data , Large Language Models , Large Scale Optimization , Machine Learning , Natural Sciences , Public Interest Tech Computational Biology
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Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated working experience
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translational medicine concepts Publication history in relevant fields (AI/ML, genetics, toxicology) Experience with deep learning frameworks and generative AI models (e.g., GANs, VAEs) Key Leadership
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed