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. Demonstrated experience establishing, directing, and expanding multi-stakeholder peer-learning networks, professional associations, or collaborative public sector cohorts. Deep knowledge of public sector data
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campus community located in the city’s cultural corridor, Buffalo State prides itself as having smaller learning environments coupled with larger university opportunities. Boasting a diverse and inclusive
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experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team
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practical application of machine learning methods (especially deep learning) Publication of scientific results in renowned international journals and conferences Teaching of courses as well as planning and
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical knowledge
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Learning and software engineering with at least 3-5 years of research experience (including PhD training) in related fields. Proven track record in research and development of cybersecurity and/or Deep
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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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parameter efficient methods, knowledge of a deep learning framework (PyTorch, JAX/FLAX or Tensorflow 2.0) and the Hugging Face ecosystem; experience of LLM observability and cost tracking; and familiarity
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selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply