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Position: PhD Student in Exploration Geophysics
Institution: Luleå University of Technology
Location: Luleå, Norrbotten County, Sweden
Duties: You will take part in the project which aim to establish a prototype service for monitoring and forecasting geoelectric fields that drive GIC in Europe. The service will help operators to protect critical ground infrastructure vulnerable to damage caused by GIC. The service will display geographic hazard maps of near real-time and historical geoelectric fields, continuously running short-term (lead time 15-70 minutes) and long-term (lead time 2-4 days) forecasts, and a storm time mid-term (lead time 2-12 hours) forecast. The geoelectric field will be derived from full three-dimensional (3D) induction modelling of the conducting ground as driven by realistic external geomagnetic variations. The short-term forecast will rely on machine learning modeling of geomagnetic variations from solar wind data sampled at the Lagrange point L1. The long-term forecast will estimate the activity expected due to solar wind co-rotating interaction regions (CIRs) and high-speed streams. You will be responsible for implementing 3D induction modelling of the conducting ground as driven by realistic external geomagnetic variations
Requirements: You must have a M.Sc or equivalent degree in geophysics, mathematics, physics, geology or other relevant subject. Good understanding of theory and numerical methods used in modelling and inversion is required. Experience in software development (Python in particular) and management of large data sets is important. You are expected to work in a team and are open to collaborate with colleagues and external partners. Fluent written and spoken English is required
   
Text: PhD Student in Exploration Geophysics You will take part in the project which aim to establish a prototype service for monitoring and forecasting geoelectric fields that drive GIC in Europe. The service will help operators to protect critical ground infrastructure vulnerable to damage caused by GIC. The service will display geographic hazard maps of near real-time and historical geoelectric fields, continuously running short-term (lead time 15-70 minutes) and long-term (lead time 2-4 days) forecasts, and a storm time mid-term (lead time 2-12 hours) forecast. The geoelectric field will be derived from full three-dimensional (3D) induction modelling of the conducting ground as driven by realistic external geomagnetic variations. The short-term forecast will rely on machine learning modeling of geomagnetic variations from solar wind data sampled at the Lagrange point L1. The long-term forecast will estimate the activity expected due to solar wind co-rotating interaction regions (CIRs) and high-speed streams. You will be responsible for implementing 3D induction modelling of the conducting ground as driven by realistic external geomagnetic variations You must have a M.Sc or equivalent degree in geophysics, mathematics, physics, geology or other relevant subject. Good understanding of theory and numerical methods used in modelling and inversion is required. Experience in software development (Python in particular) and management of large data sets is important. You are expected to work in a team and are open to collaborate with colleagues and external partners. Fluent written and spoken English is required
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