About this role
The Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, is establishing the Onsager Fellowship programme to attract young scholars with a solid reputation for high-quality research, http://www.ntnu.edu/onsagerfellowship.
As part of this fellowship program, NTNU invites applications for a tenure-track associate professorship in Statistical Machine Learning, affiliated with the Department of Mathematical Sciences<http://www.ntnu.edu/imf> . The department has 38 full professors and 9 associate professors. In addition there are 1 adjunct professor, 6 adjunct associate professors, about 20 postdoctoral fellows and about 65 doctoral students. There are 7 women in tenured positions. The department has five research groups: algebra, analysis, differential equations and numerical analysis, geometry and topology, and statistics.
Company:
Norwegian University of Science and Technology
Qualifications:
The new position is in the field of statistical machine learning. The holder of this position is expected to serve as a bridge between machine earning and the existing research activities of the statistics group and the research group in Bayesian computing in particular. Besides doing research, the successful applicant is expected to give courses and supervise students at bachelor, master and PhD level. We are seeking candidates who carry out excellent research at the boundary of statistics and machine learning, and who have a PhD in one of the disciplines. The evaluation of candidates will emphasize a strong background in statistical theory relevant for machine learning. An excellent teaching record will be considered an advantage.
Specific requirements:
This is a tenure-track position at an associate professor level, with applicants expected to have demonstrated world-leading research capability in the field. It is expected that the successful applicant will qualify for full professorship after the tenure-track period of 6-7 years.
Educational level:
Ph. D.
How to apply:
Please mention NLP People as a source when applying