The aim of the postdoctoral research fellowship is to advance the state-of-the-art in machine learning techniques for time series modelling, classification and prediction. The work can either focus on fundamental issues such as novel learning algorithms and knowledge representation, or on applications such as health care, energy, safety and security, fraud detection, astronomy, human-computer interaction, bioconservation and others depending on the successful candidate’s interests and experience.
The successful applicant should hold a PhD in a related field (e.g. machine learning, artificial intelligence, data mining). To be considered for the position, applicants must have an approved PhD thesis by the closing date of the announcement.
Personal suitability, good teamwork skills, inventiveness, and a proactive approach will be emphasised in the evaluation as well as relevant practical experience. The Post-Doctoral Research Fellow will be expected to contribute to an active research community that promotes the personal and professional growth of the post-doctoral candidate. The position places great demands on the applicant’s capacity for independent goal-oriented work, ability to concentrate and attention to detail.