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

Job advertisement PhD position: Model informed data acquisition for emission flux estimation using 4-dimensional variational data assimilation

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PhD position: Model informed data acquisition for emission flux estimation using 4-dimensional variational data assimilation

Position
PhD position: Model informed data acquisition for emission flux estimation using 4-dimensional variational data assimilation

Employer
Research Center Juelich logo

Research Center Juelich

Homepage: https://www.fz-juelich.de/iek/iek-8/EN/


Location
Juelich, Germany

Sector
Academic

Relevant division
Atmospheric Sciences (AS)

Type
Full time

Level
Entry level

Salary
Open

Required education
Master

Application deadline
Open until the position is filled

Posted
21 December 2021

Job description

You want to apply your data science knowledge to the basic research questions and societal challenges of our modern world? Our scientists in HDS-LEE address some of the most pressing issues of our time, such as energy transition, climate change and resource scarcity, brain function, drug design, identification of diseases at very early stages. As Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE), we aim to educate and train the next generation of data scientists during their doctoral thesis in close contact to domain-specific knowledge and research in three application domains: Life and medical science, earth science, energy systems and material science. Visit HDS-LEE.

Air pollution is the number one environmental health risk. Therefore quantitative understanding of sources and causes of poor air quality are highly relevant for the development of strategies to improve air quality. The atmospheric modeling group of the Institute of Energy and Climate Research (IEK-8) at Forschungszentrum Jülich performs detailed investigations of the emission fluxes of atmospheric constituents using the 4-dimensional variational (4D-var) data assimilation method implemented in the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM). In atmospheric chemistry modeling, the 4D-var method is a powerful tool to assess the state of the atmosphere and the corresponding emissions that are in compliance with observations. Various observational data sets used for the analysis are based on in situ measurements and remote sensing platforms. Find more Information about the IEK-8 here.

In our regional modelling group we are offering, supervised by Prof. Dr. Astrid Kiendler-Scharr, a

PhD position: Model informed data acquisition for emission flux estimation using 4-dimensional variational data assimilation

Your Job:

Observations of atmospheric constituents provide detailed information about the state of the atmosphere but lack in temporal or spatial resolution. Numerical models provide a temporally and spatially resolved analysis of the atmosphere but lack of accuracy due to various uncertainties in the input data. Data assimilation methods enable to combine observational accuracy and model resolution for reliable analyses of the atmosphere. However, the information content of many diverse observations from different platforms on the analyses remains unclear.

The aim of the PhD-project is to setup an optimal experimental design method to optimally sample from the heterogeneous observational data as input for the EURAD-IM data assimilation system. Therefore, the information content of different observing systems is analysed with focus on emission flux and model state estimations.

  • The successful applicant is expected to perform detailed 4D-var analyses using the EURAD-IM to identify observational setups as an optimal input to the analysis.
  • By this optimal data acquisition, the assimilation system gains efficiency in estimating the emission fluxes, which needs to be evaluated.
  • In addition to the observability assessment, the EURAD-IM is analyzed for potential causes hindering the efficient optimization procedure.

Your Profile:

  • You have a high interest to apply your data science knowledge to regional, inverse modelling of air quality
  • M. Sc. degree in physics, mathematics, meteorology, or a related field
  • Experiences in data science, data assimilation, big data analyses, or deep learning methods are of great advantage
  • Good knowledge in software development using FORTRAN90 or Python
  • Experiences on high performance computing (HPC) are of advantage
  • Good skills in the spoken and written English language: TOEFL or equivalent evidence of English-speaking skills
  • Outstanding organizational skills and the ability to work independently
  • Very good cooperation and communication skills and ability to work as part of a team in an international and interdisciplinary environment
  • A high level of scholarship as indicated, for example, by bachelor and master study transcripts and two reference letters

Our Offer:

This HDS-LEE PhD position will be located at Forschungszentrum Jülich. The successful candidate will be part of the regional modelling group and will be supervised by Prof. Dr. Astrid Kiendler-Scharr.

  • Outstanding scientific and technical infrastructure – ideal conditions for successfully completing a doctoral degree
  • A highly motivated group as well as an international and interdisciplinary working environment at one of Europe’s largest research establishments
  • Continuous scientific mentoring by your scientific advisors
  • Chance of participating in (international) conferences
  • Unique HDS-LEE graduate school program
  • Qualification that is highly welcome in industry
  • Further development of your personal strengths, e.g., via a comprehensive further training program; a structured program of continuing education and networking opportunities specifically for doctoral re-searchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs
  • Targeted services for international employees, e.g. through our International Advisory Service

The position is initially for a fixed term of 3 years. Pay in line with 75% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund). Further information on doctoral degrees at Forschungszentrum Jülich including our other locations is available here.

Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.

We also welcome applications from disabled persons.

In case of any question arise, please contact Dr. Philipp Franke (p.franke@fz-juelich.de)


How to apply

Please apply here.