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results. Preferred Qualifications: Experience with generative AI deep learning and active involvement in data science and machine learning projects. Experience in neural network architecture, cloud
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Enthusiasm in the Deep learning and AV related research Proficient in paper writing and presentation Possess strong analytical and critical thinking skills Able to build and maintain strong working
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the deadline for applications is required, in the contracting phase, including those resulting from academic degree recognition processes. Preferred factors: Knowledge of Machine and Deep Learning; Knowledge in
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from academic degree recognition processes. Preferred factors: Knowledge of Machine and Deep Learning; Knowledge in data exploration and processing; Knowledge of Generative AI models n mainly LLM's
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, leveraging advanced learning analytics, machine learning, and deep learning techniques. The candidate shall work under the supervision of the Principal Investigator (PI) and Co-PIs to conduct academic research
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/rehabilitation applications. It is expected that the application has the knowledge of: 1) deep learning, large AI models, large language models; 2) the rendering techniques for generating human body animations
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hardware design (Verilog/VHDL), FPGA-based acceleration, etc. Experience with deep learning frameworks like PyTorch, Keras, or TensorFlow, and tools such as Jupyter Notebook, is expected. A strong foundation
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, NeurIPS, ICML, ICLR, and etc. Experience in interdisciplinary studies of deep learning, mathematics, and physics is preferred. Strong theoretical background in quantum learning theory, quantum many-body
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expertise in the following areas: Machine Learning in general, with an emphasis on deep learning and language modeling Model benchmarking and evaluation pipelines for NLP/LLMs Domain-aware application of AI
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workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness