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Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via imaggeo.egu.eu)

Job advertisement PhD student in Ecosystem modelling

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European Geosciences Union

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PhD student in Ecosystem modelling

Position
PhD student in Ecosystem modelling

Employer
Department of Physical Geography, Stockholm University logo

Department of Physical Geography, Stockholm University

The Department of Physical Geography is one of the major departments within the Faculty of Science. The department has approximately 115 employees and educates approximately 1 000 students annually. Education is oriented towards geography, geosciences, biology-earth sciences, and environmental protection and environmental management. The main research areas are: Landscape, Evironment and Geomatics, Climate Science and Quaternary Geology, Geomorphology and Glaciology, and Water, Permafrost and Environmental systems.

Homepage: https://www.natgeo.su.se/english/


Location
Stockholm, Sweden

Sector
Academic

Relevant divisions
Biogeosciences (BG)
Hydrological Sciences (HS)
Soil System Sciences (SSS)

Type
Full time

Level
Student / Graduate / Internship

Salary
Open

Required education
Master

Application deadline
8 October 2021

Posted
6 September 2021

Job description

The PhD project focuses on modelling ecosystem processes and in particular microbial-plant interactions. Microbial processes have global-scale impacts, including climate regulation and provision of nutrients to plants, but how microbes and microbial-plant interactions respond to changes in soil resources remains challenging to understand and quantify with models. We thus need to improve the predictability of carbon and nutrient cycling. To address these challenges, this PhD project will explore theoretical approaches towards a holistic description of how microbial-plant interactions shape ecosystem dynamics.

The selection among the eligible candidates will be based on their capacity to benefit from the training. The following criteria will be used to assess this capacity: the candidates’ documented knowledge in the relevant field of research, written and oral proficiency in English, the capacity for analytical thinking, the ability to collaborate, as well as creativity, initiative, and independence. The assessment will be based on previous experience and grades, the quality of the degree project, references, relevant experience, interviews, and the candidate’s written motivation for seeking the position.

Specifically, the candidate should be interested in developing theory and linking models and empirical data in the context of soil and ecosystem biogeochemical cycles (especially microbial-plant interactions). Proven experience in developing mathematical models (e.g., dynamical system theory, mass and energy balance equations), and working knowledge of Matlab, R, Python, Mathematica, or other programming languages for model implementation are required. A MSc thesis or any publications demonstrating these mathematical and modelling skills is a merit.


How to apply

Apply for the PhD student position at Stockholm University’s recruitment system:

https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=15777&rmlang=UK

Please include the following information with your application

Your contact details and personal data Your highest degree Your language skills Contact details for 2–3 references

and, in addition, please include the following documents

Cover letter CV – degrees and other completed courses, work experience and a list of degree projects/theses Project proposal presenting the applicant’s view on: – state of the art on the project topic described in the advertisement (max half page) – knowledge gaps that need to be addressed (max half page) – proposed approach to fill the identified gaps and how it is related to the applicant’s knowledge/expertise and previous experiences (max one page) Degree certificates and grades confirming that you meet the general and specific entry requirements (no more than 6 files) Letters of recommendation (no more than 6 files) Degree projects/theses (no more than 6 files).