are welcome, or strong expertise in one and keen interest in working with expert colleagues on the others: automatic experimental design, Bayesian inference, human-in-the-loop learning, advanced user modelling, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, simulator-based inference, likelihood-free inference. There will be particularly good opportunities More ❯
involves AI4Science and for health, sequential decision making and experimental design under uncertainty, and collaborative AI. Machine learning keywords include Bayesian inference, distribution shifts, generative modelling, human-in-the-loop learning, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulation-based inference. The positions come with excellent opportunities for More ❯
an AI Data Annotator, you will: Transcribe and annotate audio recordings across various dialects and languages. Perform quality assurance and validation of machine-generated transcripts, utilising human-in-the-loop and RLHF processes. Work on training data for developing and current ASR, TTS, sentiment analysis, emotional tone detection, and preference modelling tasks. Collaborate with linguists, engineers More ❯
confidentiality. What You'll Be Doing? Transcribe and annotate audio recordings across various dialects and languages. Perform quality assurance and validation of machine-generated transcripts, utilising human-in-the-loop and RLHF processes. Work on training data for developing and current ASR, TTS, sentiment analysis, emotional tone detection, and preference modelling tasks. Collaborate with linguists, engineers More ❯
