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PhD Stipend/Integrated Stipend in representation, compression, learning, and inference for classical and quantum data. At the Technical Faculty of IT and Design, Department of Computer Science, one
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statistics This PhD project falls under the collaboration between Research Thrust RT2 Physics-based models, and Research Thrust RT3 on representation, compression, learning, and inference. For long-distance
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lightweight AI models suitable for real-time execution on constrained platforms using techniques such as model compression, quantization, and hardware-aware neural network design. Investigating mechanisms
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analyzes video recordings to identify these subtle cues. This advancement helps therapists gain a better understanding of their clients and the psychotherapy process, ultimately improving mental health
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personalised media experience, as formulated in SMPTE ST 2110 suite of standards for video, audio and data over IP. This research asses the implications for public interest media of these fundamental changes and