Udsendt dato16. september 2023
Udløbsdato5. oktober 2023
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Environmental Science programme. The position is available from 01 December 2023 or later.
Assessing future changes in Greenland runoff using machine learning and climate models
Research area and project description:
We seek a candidate for a fully-funded PhD project investigating the range of present and future runoff from Greenland under different climate scenarios. Output from high-resolution regional climate models and in-situ observations of runoff will be used to develop machine learning tools that can provide estimates of future runoff, with a combination of in-situ and satellite data to evaluate the approach. The project is a collaboration between Aarhus University, the Geological Survey of Denmark and Greenland (GEUS), and the National Centre for Climate Research (NCKF) at the Danish Meteorological Institute (DMI).
Runoff from Greenland includes components from the ice sheet, marginal glaciers and non-glaciated land surfaces. Temporal and spatial runoff variability can impact infrastructure (buildings, bridges and roads), security of supply (energy, water), industry/production, as well as fisheries and marine ecosystems. The potential impacts are emphasized with ongoing and future warming in the Arctic and knowledge of the runoff is therefore critical both for climate adaptation planning and mitigation efforts in and outside the Arctic.
State-of-the-art model simulations show a wide variation in melt and runoff estimates in the near future. While runoff calculations from high-resolution climate models are important to determine future potentials, there is still a limited number of simulations available, and these do not sample the full range of outcomes. At the same time, there is only limited observational data to assess these model simulations.
This project will therefore develop machine learning-based tools to be applied to different global and regional climate model outputs to produce an ensemble of medium- to long-term projections (2050 to 2150) of runoff under a range of future scenarios, allowing a statistical assessment of the likely range in future runoff.
This project offers the opportunity to work with research that will contribute to climate adaptation in Greenland and Denmark. International and domestic collaboration is essential and some fieldwork in Greenland can be expected. We seek a motivated and independent student with well-developed numerical skills and ideally experience in the field of machine learning. The candidate should expect to be situated both at DMI in Copenhagen and Aarhus University in Roskilde.
Project description. For technical reasons, you must upload a project description. Please simply copy the project description above, and upload it as a PDF in the application.
Qualifications and specific competences:
* MSc education in physics, maths, computer science, geophysics, engineering, glaciology, environmental science or a related subject.
* Well-developed numerical skills and ideally experience in developing and using machine learning models.
* Experience in programming, data analysis and visualisation in Python, R, Julia, Matlab or similar.
* Experience with climate model output or large observational datasets of climatic variables as well as knowledge of the Arctic climate system and climate change are further advantages.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Risø, Frederiksborgvej 399, 4000 Roskilde, Denmark
Applicants seeking further information are invited to contact:
- Professor Peter L. Langen, [email protected] (main supervisor)
How to apply:
Please followthis link to submit your application. Application deadline is 05 October 2023 23:59. Preferred starting date is 01 December 2023.
For information about application requirements and mandatory attachments, please see our application guide.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
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