Phd Candidate Advancing Space Weather Predictability
il y a 2 semaines
Computing
Job Type
PhD Position
Employment - Hours
Full time
Duration
Fixed term
Qualification
Masters
Sector
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Job Details:
About the SnT
SnT is a leading
international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent.
We're looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you've come to the right place
Your Role
Space weather, similar to weather on Earth, has a significant effect on infrastructure in space and on Earth. For example, solar storms may obstruct radio communication on Earth and space.
Severe space weather events may even lead to failures of the electric grid, causing significant economic damage and posing a threat to societal stability.
As weather forecasts on Earth, space weather forecasts may help to mitigate and prepare for such space weather events. Recently, the use of machine learning for improved space weather forecasting has gained in importance.
The Luxembourg-based company Mission Space and SnT, University of Luxembourg are joining forces to develop a space weather center of excellence.
The first building block is to improve the accuracy of space weather forecasting using a combination of existing space weather models and data collected in space.
For the latter, Mission Space will soon launch a dedicated satellite constellation for acquiring space weather data in space.- **Geomagnetic indices analysis
for time series behavior extrapolation** into the near future (flux, indicators, indices). The objective is to discover patterns in the time series that are correlated with solar particle events in the magnetosphere. Then, we would use these patterns as a learning base to estimate the probability of occurrence of solar particle events connected to these patterns. Thus, it is desirable that the to-be-developed machine learning models are interpretable, or at least that their prediction can be justified through explainable AI techniques. The end goal is to enhance event criteria, which are currently based on threshold values (NOAA). Open-source data are available to support the research. To facilitate the start-up of the research project, Mission Space can also provide terminology table and "fresh publication" that the student can consult to increase his knowledge of the field
- Use of
secondary indices: new combinations, based more on LEO/ground measurements than on solar wind parameters. The use and the automated forecasting of secondary indices could improve the time series and lead to better predictions
Your Profile
Competences / Experience:
You should have some knowledge and experience in some of the following topics:
- Space weather models and tools
- Machine learning, in particular, time series forecasting
- Excellent programming skills
- Strong team working and interpersonal skills
- Pragmatic, resultoriented
- Excellent written and oral communication skills
- Carrying out research in the predefined areas
- Disseminating results through scientific publications
- Assisting in the organization of relevant events and workshops
Qualification:
A MSc. degree or equivalent in Computer Science
Programming Skills:
Python mandatory. Experience with Java, Matlab, LabView, or another programming language is an asset
Language Skills:
Fluent written and verbal communication skills in English are required
Here's what awaits you at SnT
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A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance
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Exciting infrastructures and unique labs. At SnT's two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
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The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 55 industry partners
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Multiple funding sources for your ideas. The University supports researchers to acquire funding from national, European and private sources
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Competitive salary package. The University offers a 12 month-salary package, over six weeks of paid time off, meal vouchers and health insurance
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Be part of a multicultural family. At SnT we have mor
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