Job
- Level
- Erfahren
- Job Feld
- Data, Application
- Anstellung
- Vollzeit
- Vertragsart
- Befristetes Dienstverhältnis
- Ort
- Jülich
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In diesem Job entwickelst du ein datenbasiertes Modell zur Ableitung von Luftschadstoffen aus Satellitendaten, führst Fehleranalysen durch, implementierst diese in Datenassimilation und überprüfst deren Integration in Luftqualitätsmodelle.
Job Technologien
Deine Rolle im Team
- To make reliable predictions and analyses of air pollution, data assimilation methods, which integrate observational data into model simulation to update the model state and the underlying parameters, are inevitable.
- Specifically, the improvement of emission inventory data by data assimilation applications has demonstrated strong positive impact on the analysis' performance.
- However, recent studies have demonstrated the limitations of current ground- and satellite-based observational networks.
- The PhD project aims for a new method to derive ground-level concentrations from satellite-based measurements and additional data.
- Specifically, the project's objective is to develop a data-driven method that maps satellite-derived data to ground-level concentrations for air pollutants such as NO2 (nitrogen dioxide), CO (carbon monoxide), and SO2 (sulfur dioxide).
- The methodology will be embedded into the data assimilation workflow of the European Air pollution Dispersion-Inverse Model (EURAD-IM).
- Focus will be placed on the Sentinel-5P TROPOMI (Tropospheric Monitoring Instrument) data, which is available since 2018 and thus provides a big dataset.
- However, the transferability to Sentinel 4 and 5 data recently launched in July and August 2025 will be explored.
- All this has the potential to enhance the performance of emission data analyses to the next level.
- The outcome of the project is twofold.
- Firstly, the project aims at developing a method that can derive ground-level concentrations of air pollutants on a high spatial resolution directly from satellite retrievals.
- Secondly, the outcome of this research will enable the sampling of satellite data to identify an optimal subset of observational data for optimizing the emission inventory data.
- Analyses of these emission corrections will be performed with the four-dimensional variational data assimilation (4D-var) system within the chemistry-transport-model EURAD-IM.
- The simulation improvements due to optimized emission data will be evaluated with independent observations, such as vertical profile data from the In-service Aircraft for a Global Observing System (IAGOS).
- The project will be conducted as a collaboration of the Air Quality and Emission Optimization group at the Institute of Climate and Energy systems (ICE-3) at Forschungszentrum Jülich and the group working on Methods for Model-based Development at RWTH Aachen.
- The PhD candidate will be based at Forschungszentrum Jülich where the scientific focus on atmospheric research is placed.
- To exchange and deepen the collaboration in particular with respect to methodological approaches of data-driven solutions, at least two short but intensive research stays at RWTH Aachen are planned.
- It is envisioned that this strengthens the communication and advances the progress of research.
- Your tasks involve:
- Developing a machine learning-based model to map satellite retrievals to ground based air pollutant concentrations
- Conducting error assessment on the derived concentration data
- Implementing new observational data into an operational data assimilation system
- Evaluating potentials and limitations of the integration of the derived data for air quality modelling and analyses
- Presenting research results at national and international conferences
- Preparing and contributing to scientific publications
Unsere Erwartungen an dich
Ausbildung
- M. Sc. degree in meteorology, physics, mathematics, or a related field
Qualifikationen
- Mandatory qualifications are:
- Good knowledge in data handling and machine learning
- Good knowledge in software development, data processing and visualization with Python
- Strong interest in atmospheric physics, chemistry, atmospheric modelling, and observations
- 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
- Of great advantage are:
- Basic knowledge of data assimilation
- Knowledge of FORTRAN programming language
- Please feel free to apply for the position even if you do not have all the required skills and knowledge.
- We may be able to teach you missing skills during your induction.
Erfahrung
- Experiences in numerical modelling
- Experiences on high performance computing (HPC)
Unser Angebot
- We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change!
- This HDS-LEE PhD position will be located at Forschungszentrum Jülich and RWTH Aachen.
- We offer ideal conditions for you to complete your doctoral degree:
- Outstanding scientific and technical infrastructure
- A highly motivated group as well as an international and interdisciplinary working environment at one of Europe's largest research centres
- Continuous scientific mentoring by your scientific advisors
- Chance of participating in international conferences
- Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats)
- 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 researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors
- 30 Days of annual leave and flexible working arrangements, including partial remote work
- Targeted services for international employees, e.g. through our International Advisory Service
- Access and work on one of the world's leading HPC infrastructures at JSC
- The position is initially limited to three years, with a planned one-year extension.
- Pay in line with 75% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60 % of a monthly salary as special payment ("Christmas bonus").
Benefits
Work-Life-Integration
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Forschungszentrum Jülich GmbH
Forschungszentrum Jülich ist Mitglied der Helmholtz-Gesellschaft und trägt dazu bei, die wichtigsten gesellschaftlichen Herausforderungen in den Bereichen Information, Energie und Bioökonomie zu lösen.
Description
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Bildungswesen, Wissenschaft, Forschung
PhD position - Smart preparation of air pollutant satellite retrievals
- Ort
- Jülich
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
