Postdoctoral Research Fellow in Statistics / Data Science
One position as Postdoctoral Research Fellow (SKO 1352) in statistics is available at the Department of Mathematics at the University of Oslo.
The postdoctoral research fellowship is affiliated with Big Insight and the research activity of the candidate will be within the center. Big Insight develops original statistical and machine learning methodologies and analytical and computational tools to extract knowledge from complex and big data, addressed towards innovation. Rather than being merely purely data driven, the center investigates approaches that exploit statistical models describing dynamics, mechanisms and structures of the underlying processes. Among the research themes which might be interesting for the postdoctoral fellow we mention, among others, high dimensional data, streaming data, (model based) machine learning, Bayesian inference, complex dependency modeling, computationally intensive inference.
Big Insight research projects are in close collaboration with industrial and public partners, which are a source of exciting challenges, important problems and unique data. Methodological developments in modern statistics and machine learning are very often motivated by challenging applied problems and Big Insight offers an ideal framework. The postdoctoral fellow is expected to take interest in, and actively take part in these collaborations.
In collaboration with faculty members and relevant partners, the post doctoral fellow is expected to contribute to the management and organisation of the project, by taking direct responsibilities in administrative and leading tasks. She/he will be responsible for progress, developing methodology, implementing algorithms and producing scientific results of substantial interest, published in top peer-reviewed scientific journals.
More about the position
The fellowship period is for three years, with a starting date to be agreed upon (in 2019).
This is an opportunity to join one of Europe's most active statistics and data science communities. The Section for Statistics and Data Science at the Department of Mathematics currently includes 9 full time academic positions in statistics, 6 adjunct positions and several PhD students and post doc’s, making up a group of about 30. Statistics at UiO is internationally recognized, with interests spanning a broad range of areas (including high-dimensional and big data, nonparametric inference, algorithmic methods, Bayesian inference, statistical computing, model selection, time-to-event models, space-time models and copula models) and applications (e.g. genomics, sensor data, anomaly and fault detection, text processing).
The section has a major role in the center for research-based innovation Big Insight, a consortium of 15 academic, industrial and public partners, with a funding of about 4 million Euro annually in the period 2015-2023. Big Insight and the University of Oslo offer a lively and socially rewarding environment, with many common activities, a broad visitor program, as well as solid travel funding.
The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
- Applicants must hold a degree equivalent to a Norwegian doctoral degree in statistics or machine learning, or in a related quantitative subject with proven competence in these areas. Doctoral dissertation must be submitted for evaluation by the closing date. Appointment is dependent on the public defence of the doctoral thesis being approved.
- Fluent oral and written communication skills in English
The following qualifications will count in the assessment of the applicants:
- Excellent results in the MSc and PhD studies are required
- Experience with statistical modelling of large, complex data is a prerequisite
- Candidates to the position will have experience and/or clear potentials to initiate, develop and manage an independent scientific programme
- Proficiency with programing languages (R, Matlab, Python, C++ or others) is necessary
- Candidates must also demonstrate team spirit in developing their research, with strong interpersonal skills
For more information click "LINK TO ORIGINAL" below.