We are looking for a postdoctoral researcher familiar with machine learning, ideally neural networks implemented with pytorch, to work on unsupervised transfer learning for biomedical time series. In our group, 'Biomedical Machine Learning' (BIML) at Department of Electrical and Computer Engineering, Aarhus University, we have recently begun developing a new method for unsupervised transfer learning, which we have been testing on wearable EEG data (we are closely connected with the Center for ear-EEG). The results are very promising, though there exist multiple challenges still before we have realized the method's full potential. We are now looking to fill a 1-year post doc position to continue this work. Work is on-going to secure additional funding for extending the position further. The primary requirement for the candidate is familiarity with deep learning (ideally the pytorch framework), though experience with transfer learning, or EEG data, or sleep monitoring, is a plus. If this is interesting, please see the full job posting here: Post Doc in machine learning for biomedical time series and sleep, Department of Electrical and Computer Engineering, Aarhus University - Ledig stilling på Aarhus Universitet (au.dk) <https://www.au.dk/om/stillinger/job/post-doc-in-machine-learning-for-biomedical-time-series-and-sleep-department-of-electrical-and-computer-engineering-aarhus-university> Note that the starting date is somewhat flexible (an earlier start should be possible). Regards Kaare Mikkelsen, Assoc. Prof. Department of Electrical and Computer Engineering Aarhus University --------------------------------------------------------------------