Job date: 2015-04-15
End Date:
Company : Norwegian University of Science and Technology Country : Role : Student
Associate Professor (Onsager Fellowship) in Statistical Machine Learning
NTNU is establishing the Onsager Fellowship programme, which is designed to attract the most talented young scholars with an established reputation for high-quality research and a commitment to teaching at university level. The programme represents the introduction of tenure-track positions in the Norwegian university system.
NTNU's Faculty of Information Technology, Mathematics and Electrical Engineering hereby invites applications for a tenure-track associate professor position in Statistical Machine Learning as part of the Onsager Fellowship programme, affiliated with the Department of Mathematical Sciences.
Job description
The position will be associated with the statistics group at the Department of Mathematical Sciences. The current research in statistics includes computational statistics, biostatistics, industrial statistics, population biology, spatial statistics and theoretical statistics. A large part of the research is methodological and motivated by applications in other disciplines.
In a recent evaluation by the Norwegian Research Council, the research of the statistics group obtained the highest mark - "Excellent/World leading". The research in computational statistics includes a world-class group in Bayesian computing built around the INLA-project (www.r-inla.org), largely directed towards developing sound, reliable and fast Bayesian inference for latent Gaussian models. The research in biostatistics includes bioinformatics and genomics. In industrial statistics, the research includes extreme value statistics, experimental design, and reliability analysis. The research in population biology involves evolutionary biology, population genetics, stochastic population dynamics, and conservation biology. The research in spatial statistics involves stochastic modeling and inference for spatial and space-time phenomena, while the research in theoretical statistics includes the study of characteristic functions and methods for exact statistical inference using Monte-Carlo simulations.
The new position is in the field of statistical machine learning, and will be at the level of associate professor. The holder of this position is expected to serve as a bridge between machine learning 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.
During the tenure-track period of 6-7 years, the successful applicant will receive professional guidance, training and advice by mentors appointed by the faculty to build a successful academic career. In addition, the candidate will have no teaching load for the first year of employment. The candidate will be subject to a mid-career assessment after 3 years, and a final tenure assessment after no more than 6 years. It is expected that the candidate will qualify for a full professorship at the end of the tenure-track period.
Qualifications
Applicants must hold a PhD and will primarily be evaluated on the basis of their documented scholarly achievements. The PhD should be received no more than 5-6 years ago.
The successful applicant must have a strong academic track record, an active research program, an academic standing showing internationally competitive research, and have an internationally recognized high potential to make a future impact. The ideal applicant should have an exceptional publication record with significant first authorships. Applicants must have spent significant time in research institutions outside of Norway.
Teaching qualifications are not mandatory, but documented teaching qualifications and experience will be considered an advantage.
Application requirements
The application should contain:
CV including information relevant for the qualifications and a full list of publications with bibliographical references
Testimonials and certificates
The most important publications that are relevant for the evaluation of the applicant’s qualifications (maximum 10 publications)
A brief description of the scientific/technological relevance of the candidate's research
Research proposal for the tenure-track period of 6-7 years (maximum 10 pages)
Information about educational experience, including development of study programs, curricula, teaching experience, and development of teaching methods and the learning environment. See “Documentation of an applicant’s pedagogical qualifications”: http://www.ntnu.edu/vacancies/pedagogical-qualifications
Information about dissemination activities
Other documents which the applicant would find relevant
Joint works will also be evaluated. If it is difficult to identify the contributions from individuals in a scientific collaboration, applicants are to enclose a short summary of his/her contribution.
Following the application deadline, a shortlist of applicants will be drawn up, and all applicants will be informed whether they are placed on the shortlist. Shortlisted applicants will be evaluated by an international expert committee. The top candidates from this evaluation will be invited for interviews and trial lectures.
Formal regulations
If the candidate does not have prior formal pedagogical qualifications in university-level teaching, the candidate must complete a recognized course which gives a pedagogical qualification within the first two years of employment. NTNU offers such courses.
Proficiency in the English language should be documented. For a candidate who does not already master a Scandinavian language, the candidate is expected to attend Norwegian language courses from the start of employment. After 3 years, the candidate should have completed the basic language courses offered at NTNU. After 6 years, the candidate should be proficient in Norwegian.
Diversity is important to achieve a good, inclusive working environment. We encourage all qualified applicants to apply, regardless of gender, disability, and cultural background.
The appointment is to be made in accordance with the regulations for State Employees and Civil Servants in Norway. The candidate must adhere to regulations that concern changes and developments within the discipline and/or the organizational changes concerning activities at NTNU.
Further details about the position can be obtained from Head of Department, Professor Einar Rønquist, phone: +47 73593547, e-mail: einar.ronquist@math.ntnu.no .
The position as associate professor follows code 1011, and is remunerated according to the wage levels 57 - 77 on the Norwegian government state salary scale, with gross salary from NOK 482 500 to NOK 710 100 a year. 2 % of the salary will be deducted as an obligatory premium to the Norwegian Public Service Pension Fund.
Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.
Applications are to be submitted electronically via the "Apply Through Website" button. Preferably, all attachments should be combined into a single file.
Reference no: IME 024-2015.
Application deadline: 2015-05-25.
About the employer
The Norwegian University of Science and Technology (NTNU) in Trondheim represents academic eminence in technology and the natural sciences as well as in other academic disciplines ranging from the social sciences, the arts and humanities, medicine, teacher education, to architecture. Cross-disciplinary cooperation results in innovative breakthroughs and creative solutions with far-reaching social and economic impact.
Information about the department
The Department of Mathematical Sciences 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.
The department has a wide range of teaching responsibilities. This includes all the basic education in mathematical sciences for engineering and natural science students, Bachelor’s and Master’s programs in Mathematical Sciences, and a special Master’s program in Industrial Mathematics for engineering students. The department also plays a central role in a Master’s program for high school science teachers. The master programs enjoy ample recruitment of highly qualified candidates, and as a consequence, the same holds also for the PhD-program.
The department aims to sustain and strengthen the research activity within mathematical sciences, stimulate the development of strong research groups within pure and applied mathematics, and strengthen the capacity for supervising master- and PhD-students.
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