Job title:
POSTDOCTORAL RESEARCHER IN SPACE PLASMA PHYSICS, MACHINE LEARNING, AND COMPUTING
Company:
Job description
Offer DescriptionOne of the most intriguing open questions in astrophysics is understanding why the solar wind is so hot. The surface of the Sun is approximately 6500K, yet as we move into the Sun’s atmosphere, the temperature astonishingly rises to millions of degrees, defying intuitive expectations for an expanding gas moving away from its source of heating. To unravel this mystery, two groundbreaking space missions have been launched: Solar Orbiter and Parker Solar Probe. These missions are traveling closer to the Sun than any man-made object ever has, offering an unprecedented wealth of data. The HELIOSKILL project aims to leverage this mission data, in conjunction with fully kinetic, high-resolution simulations, to solve the holy grail of solar wind research: deriving the equation of state for the expanding solar wind. This equation will illuminate how the solar wind’s temperature evolves with other measured parameters. The approach involves applying machine learning tools designed to extract physical laws from data (either observations or simulations), potentially leading to groundbreaking discoveries in the thermodynamics of the solar wind. We are seeking highly motivated Postdoctoral Researcher(s) to participate in this FWO Project Heliophysics simulations and artificial intelligence (Helioskill).The ideal candidate preferably has experience with kinetic plasma simulations and/or data analysis from ongoing space plasma missions. This position offers a unique opportunity to contribute to a project at the frontier of astrophysical research.Responsibilities are:
- Analyze and interpret data from Solar Orbiter and Parker Solar Probe missions.
- Develop and apply machine learning techniques to derive the equation of state for the solar wind.
- Perform high-resolution particle-in-cell simulations and integrate them with observational data to enhance understanding of solar wind thermodynamics.
- Collaborate with a multidisciplinary team of researchers and contribute to research dissemination through publications and conferences.
Where to apply WebsiteRequirementsResearch Field Astronomy Education Level PhD or equivalentResearch Field Computer science Education Level PhD or equivalentResearch Field Mathematics Education Level PhD or equivalentResearch Field Physics Education Level PhD or equivalentLanguages ENGLISH Level ExcellentAdditional InformationBenefitsThe appointment is for 2 years with a possibility of extending for one more year. This is a rare opportunity to work on a high-impact project that seeks to answer one of the most significant questions in space plasmas. You will be part of CmPA (Center of mathematical Plasma Astrophysics) at KU Leuven, a leading research institution, collaborating with experts in a dynamic and supportive environment, and contributing to cutting-edge research with the potential for significant scientific breakthroughs.Eligibility criteria
- Ph.D. in Space Physics, Astrophysics, Applied Mathematics, Computer Science, or a related field.
- Expertise in at least two of the following areas: space physics, machine learning, and high-performance computing.
- Strong programming skills and experience with data analysis and simulation.
- Proven ability to work independently and as part of a team.
- A track record of research excellence, evidenced by publications in peer-reviewed journals.
Selection processFor more information please contact Prof. dr. Rony Keppens, tel.: +32 16 32 70 01, mail: or Mr. George Miloshevich, tel.: +32 16 32 14 85, mail: .
You can apply for this job no later than 31/10/2024 via theWork Location(s)Number of offers available 1 Company/Institute KU Leuven Country Belgium State/Province Vlaams Brabant City Leuven Postal Code 3000 Street Leuven GeofieldContact State/ProvinceLeuven CityVlaams Brabant StreetLeuven Postal Code3000 E-Mail[email protected]STATUS: EXPIREDShare this page
Expected salary
Location
Louvain, Brabant Flamand
Job date
Sat, 31 Aug 2024 07:04:02 GMT
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