PhD position in numerical modelling of nanoplastic pollution in the ocean

The amount of plastic in our ocean is growing rapidly, with estimates of more than 5 million metric tonnes of plastic reaching the ocean each year. This plastic infiltrates the ocean food web and thus poses a major threat to marine life. However, the understanding of the distribution, pathways and fate of plastic once in the ocean is very limited.

Plastic particles on the scales of nanometers are particularly elusive; these particles have been observed in the ocean but their origin, structure and fate is unknown. In an inherently interdisciplinary project, chemists, biologists and physicists aim to map and better understand these elusive particles that can do so much harm.

You will work within the new, focusing specifically on the numerical simulation of nanoplastic transport in the ocean. Combining High Performance Computing with advanced data science techniques, the goal of the PhD is to determine the most likely origin of the nanoplastic particles found during the fieldwork in the Atlantic Ocean.

During the project, you will be involved in:

  • developing numerical simulations of nanoplastics based on the;
  • using Bayesian statistics to back-track likely sources of nanoplastic particles;
  • collaborating with the other PhDs and Postdocs in the project to integrate the numerical modelling results with the fieldwork and labwork done at NIOZ and in the chemistry groups;
  • (optionally) participating in ocean-going fieldwork to sample nanoplastics in the Atlantic Ocean.

At the end of the PhD project, you will have:

  • a deep understanding of the scale of the problem of global plastic pollution;
  • advanced skills in numerical modelling and data analysis in python;
  • the skills to communicate your scientific results to a wide audience including peers, media and the general public.

Qualifications Our ideal candidate has a driven and collaborative spirit and:

  • an MSc in Physics, Computer Science, Applied Mathematics or a similar field;
  • strong skills in python programming;
  • the ability to cooperate within a wider and interdisciplinary research team;
  • an excellent level of written and spoken English.

Preferably you also have a proven affinity with physical oceanography and experience with software development practices such as version control and unit-testing. In addition, you bring along strong skills in advanced data science.

Closing date June 13, 2020