Senior Research Officer in EEG-Based Pain Prediction

Develop reproducible EEG processing and machine-learning methods that distinguish pain from pain-free states and generalise to unseen participants. The PaiNeuro project includes deep learning, Riemannian covariance representations, domain alignment and one-class classification under Dr Sebastian Halder.

PhD completed or near completion in computer science, electronic/biomedical engineering, neuroscience, machine learning or a related field; strong Python and scientific-computing skills; machine/deep learning for EEG or high-dimensional biosignals; rigorous participant-level validation and independent testing; effective independent/team work and strong academic communication. Time-series neural networks, Riemannian covariance methods, transfer/domain adaptation, one-class methods, MNE-Python/PyTorch/Braindecode/pyRiemann and clinical open-research experience are desirable.

Salaried PaiNeuro project role on objective pain measurement with clinical EEG, collaborating with Vestre Viken Hospital Trust in Norway. Specific funding award/source is not stated.

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