We are looking for

a PhD student who will employ advanced geostatistical methods to optimise sampling designs used in integrated catchment water quality modelling. Hydrologic and hydraulic models require input data and data for parameter calibration and validation. Data collection can be costly and must therefore be optimised to gain maximum information for a given budget. This PhD research will optimise sampling designs in space and time using statistical tools from spatial uncertainty propagation analysis, statistical sampling theory and Bayesian calibration. Various sampling design optimisation techniques will be developed and tested, by making a trade-off between the cost of data collection and model output accuracy. Testing and validation is done for a Soil Water Assessment Tool applied to a catchment in Luxembourg and for minimisation of spatial and temporal rainfall estimation errors using radar data and rain gauges for a study area in the UK.
 
This research is part of the EU-funded Marie Curie Initial Training Network project 'QUICS' (Grant agreement number 607000), in which partners from various universities, research institutes and commercial enterprises across Europe join forces to improve water quality management by assessing the uncertainty of integrated catchment model water quality predictions. The project involves twelve PhD students and four Postdocs. For more information about the QUICS project and the other PhD and PostDoc vacancies, see www.quics.eu.

We ask

a candidate with an MSc degree or equivalent in applied mathematics, statistics or hydrological/hydraulic sciences. Proven experience with statistical modelling is required. Experience with numerical modelling and programming in R or Matlab is also desired.  We expect a very good level of English, strong communication skills and ability to work in a team. Ability to travel within the network is essential, as currently the position includes secondments in Luxembourg (six months) and Bristol (three months).
 
Special requirements
Candidates must be in the first four years of their research careers and be in the possession of a degree and qualifications that allow entry to the PhD programme at Wageningen University. They must not have resided or carried out their main activities (work/studies) in the Netherlands for more than 12 months in the 3 years prior to May 1, 2015.

We offer

a fulltime employment (38 hours a week) as PhD researcher within the Soil Geography and Landscape group for 18 months with a possible extension of 30 months after a positive evaluation. The gross salary will increase from € 2125,- in the first year up to € 2717,- per month in the fourth year (based on fulltime employment). We offer a holiday bonus of 8% and an end-of-the-year bonus of 8.3% of your annual salary. In addition to this salary you will receive a mobility allowance according to the rules of the Marie Curie ITN programme.

More information

Additional information about this vacancy can be obtained from Dr.ir. Gerard Heuvelink +31 (0) 317-482716, gerard.heuvelink@wur.nl.

How to apply
Interested? Don't email directly to the person mentioned above. Please use the website to apply and upload your CV and a short motivation letter.

The deadline for applications is April 1, 2015.

We are

the Soil Geography and Landscape Group (SGL) of Wageningen University. Our mission is to improve and share understanding of soil patterns and landscape dynamics. We take an integrative approach that combines biophysical and human elements to gain insight in past, present and future system dynamics, and to support sustainable land management.
 
Wageningen University and Research Centre
Delivering a substantial contribution to the quality of life. That's our focus - each and every day. Within our domain, healthy food and living environment, we search for answers to issues affecting society - such as sustainable food production, climate change and alternative energy. Of course, we don't do this alone. Every day, 6,500 people work on 'the quality of life', turning ideas into reality, on a global scale.

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