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programming skills in Python or C++, and practical experience with deep learning libraries (e.g., PyTorch) Desirable criteria 1. Research experience in one or more of the following areas: tactile sensing
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advanced analytical and statistical techniques to extract actionable insights from complex datasets. Train, evaluate, and continuously refine deep learning and machine learning models, prioritising
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culture. This tenure-track position is dedicated to advancing cancer research through expertise in cancer data science, focusing on deep learning, artificial intelligence (AI), generative AI, large language
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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Science Programs, and MS in Computer and Information Science (https://cse.aua.am/ ) invite applications for a full-time faculty position in Machine Learning at the rank of Assistant Professor, starting in
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development. You enjoy supervising and teaching and using your excellent communication skills to inspire the coming generation develop the same deep passion you have for quantum technology. You always have an
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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with experience in clinical social work to teach required MSW practice courses and other courses (as needed) in our MSW program. This is a 9-month position that teaches the equivalent of six courses
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. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating