Ongeveer 13 uur geleden - NWO-institutenorganisatie - Utrecht
In this project you will develop optical metasurfaces that control the coupling and trapping of light in ultrathin high-efficiency solar cells. We will use …
There is an urgent need of statistical sound prediction methods for extreme weather, which often has a strong disruptive societal impact. The research project …
There is an urgent need of statistical sound prediction methods for extreme weather, which often has a strong disruptive societal impact. The research project “Probabilistic forecasts of extreme weather utilizing advanced methods from extreme value theory” is funded by NWO-TTW (the former STW) and is a collaboration between the statistics section, Delft University of Technology (TU Delft) and the R&D Weather and Climate Modelling department of the Royal Netherlands Meteorological Institute (KNMI).
The tasks involved in the post-doctoral position include:
Perform a comparative verification between the statistical forecasting methods developed by the PhD student within the project and other state-of-the-art statistical (including machine learning and extreme value theory) methods.
Develop two prototype probabilistic forecast systems for extreme weather: one for a univariate weather quantity (e.g. extreme precipitation) and one for bivariate weather events (e.g. snow and (high) wind speed). The developed forecast systems will be used by several partners, including KNMI, to improve their short-term forecasts and warnings of extreme weather.
Work closely with the current project members: Prof. dr. ir. G. Jongbloed (TU Delft), Dr. J. Cai (TU Delft), Jasper Velthoen (TU Delft), Dr. M.J. Schmeits (KNMI) and Dr. K. Whan (KNMI). You are partly based at TU Delft and partly at KNMI.
Communicate regularly with the partners on project progress.
Disseminate the results through publications in peer-reviewed journals, and presentations at international conferences.
Applicants should have the following qualifications:
PhD on statistical and/or machine learning methods including application of these methods to (big) data, preferably in a probabilistic (weather) forecasting framework
preferably knowledge of extreme value theory and/or statistical post-processing and verification methods
highly motivated and interested in meteorology
experienced in (statistical) programming, preferably in R
very good communication skills and fluent spoken and written English.
TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
For more information about this position, please contact Dr. J. Cai (email@example.com), Prof. dr. ir. G. Jongbloed (G.Jongbloed@tudelft.nl) or Dr. M.J. Schmeits (Maurice.Schmeits@knmi.nl).
Applications should include a letter of application emphasising your specific interest in and qualifications for this position, a detailed CV, a publication list and contact details of at least two references in a single PDF file entilted "Lastname, Firstname.pdf". Please e-mail your application by 10 May 2018 to P.T.M. van den Bergh, Hrfirstname.lastname@example.org.
Middels onderstaande knop kun je direct solliciteren op deze vacature.Reageer op deze vacature