Careers
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Executive Director, CERIC-ERIC (the Central European Consortium for Research Infrastructure), Trieste, Italy (deadline 20th September 2026)
CERIC-ERIC, the Central European Consortium for Research Infrastructure, is searching for candidates for the position of Executive Director as defined in article 13 of its Statute.
Executive Director Profile and Duties
The Executive Director (ED) is the executive body of CERIC-ERIC and the legal representative of CERIC-ERIC responsible for the day-to-day management. The qualifications of the ED should integrate a strong scientific and research background with proven managerial capabilities. The ED works closely with the Board of Directors (BoD) and the Chair of the General Assembly (GA) and has the specific powers to commit the Consortium based on his/her coordination tasks. The Executive Director is expected to perform a significant portion of their work in person at the premises of the Statutory seat.
More details on the job and particular tasks are in CERIC-CERIC internal regulation n.5.
Selection and Contractual Arrangements
The selection will be performed by a Committee set up by the BoD and approved by the GA. The selection committee will invite shortlisted candidates for an interview. The proposal of the selected candidates will be submitted to the GA for approval and final selection.
Upon decision of the GA, its Chair will define with the selected candidate the stipend, the contractual arrangements, including in working time at the CERIC-ERIC Statuary Seat and agile work percentage, and the detailed tasks for the final approval by GA.
The call closes on September 20th 2026 at 17:00.
Post-Doc in Atmospheric Science and Machine Learning, Netherlands Institute for Space Research (SRON), Leiden, Netherlands (deadline 1st September)
Your position
You will contribute to the newly funded COGNITO project (carbon monoxide (CO) Global aNalysis, source Identification and emission quantification using TROPOMI Observations). COGNITO aims to develop the first global, satellite-based system for detecting and quantifying carbon monoxide emissions from major urban areas and industrial facilities, with a particular focus on the iron and steel sector. By using TROPOMI observations with advanced machine learning techniques, the project will provide independent information on emission patterns and support efforts to improve emission inventories and evaluate decarbonization strategies worldwide.
Your team
You will become part of the Earth Science Group (ESG) at SRON. The ESG consists of approximately 40 scientists, postdoctoral researchers, and PhD students working on the interpretation of satellite observations, atmospheric modelling, data science, and the development of future Earth observation missions. You will join a research team specializing in the detection and quantification of atmospheric emissions using satellite observations, atmospheric transport modeling, and machine learning. The team has pioneered the use of satellite observations for identifying methane super-emitters and quantifying emissions from industrial and urban sources worldwide.
Your project
Within the COGNITO project, you will apply novel machine learning approaches to detect CO plumes in global satellite observations from TROPOMI and possibly complemented by Sentinel-5. Building on successful methodologies previously developed for methane super-emitter detection, you will create a global database of CO emission events and investigate the emission source rates from hundreds of industrial facilities and urban regions worldwide.
Your work will include:
- Apply existing machine learning algorithms for automated detection of CO plumes in satellite observations
- Building a global catalogue of CO emission events from 2018 onwards
- Quantifying emissions from cities and iron and steel production facilities using inhouse quantification tools
- Evaluating temporal variability in emissions, including seasonal cycles, operational changes, and potential signatures of industrial decarbonization efforts
- Assessment of emission quantification tools using atmospheric transport modeling
- Comparing satellite derived emissions with bottom up inventories and reporting systems
- Publishing results in leading international scientific journals and presenting your work at conferences and stakeholder meetings
The project offers a unique opportunity to work at the intersection of atmospheric science, machine learning, satellite remote sensing, and climate policy.
Position requirements
We are looking for an ambitious, highly motivated, and result driven scientist with a PhD in atmospheric sciences or a similar degree, with experience in the interpretation of atmospheric (e.g. satellite, aircraft etc.) observations and machine learning applications. Strong programming and data analytics skills are also expected. Experience with research on atmospheric CO, transport modelling and/or flux inversions is considered an asset. A highly developed proficiency in written and oral English is essential, and the candidate should be capable of working both independently and in a team.
What we offer
The position we offer at SRON is full-time for a period of two years with the possibility of a two-year extension in which you will be employed by NWO-I, The Netherlands Organization for Scientific Research Institutes. The salary will be in accordance with NWO salary scale 10, commensurate with your education and experience, be for a maximum of €5.758,- gross per month on a full-time basis.
NWO-I has good secondary employment conditions such as:
- An end-of-year bonus of 8,33% of the gross yearly salary;
- A holiday allowance of 8% of the gross yearly salary;
- 42 days of vacation leave per year on a full-time basis;
- Compensation for commuting expenses;
- An excellent pension scheme;
- Options for (additional) personal development;
- Excellent facilities for parental leave;
- Ample training opportunities;
- Possibility of flexible working hours;
Due date for first selection of applications is September 1st 2026, after which the position remains open until filled.