Researcher: predictive mapping using Ensemble Machine Learning

Application Deadline: 24th of November 2019
Possible start date: 1st of January 2020
Duration: 1.5+ years,
Job location: Agro Business Park 10, Wageningen
Bruto monthly salary: The gross monthly salary starts at € 2.615,- (bonus payments are possible; part-time appointments are possible)
Job type: Research assistant / post-doctoral researcher
Fields: predictive soil mapping, R spatial, geoinformatics, pedometrics, environmetrics
Employer: EnvirometriX BV

Job description

EnvirometriX innovation, research and consultancy, Wageningen, the Netherlands, is looking for an applied researcher in the field of pedometrics, environmetrics, geo-computation and geoinformatics (programming in R, Python, Julia and similar), specifically focused on using state-of-the-art Machine Learning algorithms to implement automated methods of spatial interpolation and/or prediction, organize prediction using large Earth Observation data sets (MODIS, Sentinel, Landsat) and implement parallelisation in cluster or cloud infrastructures. You would work for EnvirometriX and OpenGeoHub on global and regional predictive soil and vegetation mapping projects where the focus is on delivering spatial and/or spatiotemporal predictions of variables of interest in a cost-effective way.

You would spend a significant amount of time computing and processing spatial data using EnvirometriX internal infrastructure and the outsourced web-services (OVH, Amazon AWS). Specific tasks include: installation of software under Linux OS, data preparation, model building and fine-tuning of Ensemble Machine Learning, parallelization, and back-end development. You would also actively contribute to the data portal and similar.

Your profile

Minimum requirements:

  • You have a MSc and/or PhD degree in the field of geoinformatics, geo-information science, environmental sciences, statistics, pedometrics and/or computer science.
  • You have excellent knowledge of FOSS including Linux OS, programming languages R and/Python.
  • You have sufficient background knowledge of statistical and machine learning (regression and classification modeling, environmetrics, pedometrics, biometry).
  • You have experience with optimizing predictive mapping frameworks (through R packages caret, mlr packages or similar).
  • You enjoy debugging code (github, gitlab), doing back-end development, and increasing the mapping accuracy by fine-tuning models and trying new algorithms.
  • You know how to organize ML benchmarking and select the optimal models.
  • You are fluent in English.



Questions regarding this position can be directed to Tom Hengl, email: 

Applications, including (1) a CV, (2) a statement of your interest and vision, and (3) self-assessment based on the minimum requirements, should be uploaded via this link. Read more about the general submission procedure.

Our offer

We offer a 1.5 years position, with possible extension, within a very stimulating international innovation and research environment. You will work in a dynamic ecosystem with enthusiastic colleagues.

  • The gross monthly salary starts at €2.615,- (with possible bonus payments);
  • Minimum of 29 holidays if in full-time employment;
  • Professional and personal development programs (up to 2 days per week for personal development);

We strongly encourage a high degree of responsibility and independence, while collaborating with close colleagues through virtual groups (Mattermost, WhatsApp). Flexi-hours and remote working is also possible.

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