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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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Department of Computer Science and the Data Science Institute. Learn more about the lab and its research here: https://nunez-comp-mental-health-cancer-care.github.io/ . RESPONSIBILITIES Reporting to Dr. John
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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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environment to study these topics given its expertise in Machine and Deep Learning, Computer Vision, Signal Processing, and Multimedia. Also, its declared vision to work especially in presence of imperfect data
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the field of frugal or green AI TECHNICAL SPHERE You have a proven experience in frugal, green or low-resource AI Strong grasp of deep learning architectures (CNN, RNN, Transformers, LLMs). Experience in fine
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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
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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Sessional Lecturer - CTL5704H - Special Topics in Teaching - Urban Education Curriculum and Pedagogy
stakeholders (including school educators, administration, community partners, professional networks). Deep knowledge and experience in contexts, policies and practices of the three divisions (Primary/Junior K-Gr
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-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment. PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA) The mission of the UNLV Office of Postdoctoral
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, physical chemistry, or surface chemistry) or related field completed by the start date Strong postdoctoral training in polymer-based materials, surface characterization, or sensor technologies Demonstrated