As a previous geoscientist student at Aarhus university, I have been priviliged to be involved in exciting projects throughout the 5 years I have been enrolled.
The degree has brought me through a large variety of courses such as geophysics, astrophysics, planetary sciences, geohazards, environmental science, climate change, renewable energy, machine learning, satellite operations, construction and programming.
During my bachelor thesis, I worked on the pre-assembly phase of the Delphini-1 cubesat. Outlining the satellites capabilities, orbit duration, re-entry time, data transfer and the possibilities of future scientific missions by simulating different scenarios. After finishing my bachelor thesis I enrolled in the masters program and continued in the satellite workshop. This allowed me to join the team assembling the satellite in a cleanlab. l also joined the software team where I programmed a satellite tracking system in python and experimented with CSP programming as well as gaining knowledge within the Linux OS.
The satellite went into space onboard the SpaceX Falcon9 rocket to the ISS, known as the CRS-16 mission, on the 5th of December 2018.
Due to my bachelor thesis and its reception at the engineering and physics department, I was recruited to co-author a paper related to heliophysics, satellite data and machine learning. The project was to establish whether or not solar flares were to be associated with coronal mass ejections and solar energetic particles. The paper was published in the Astrophysical Journal
The work I did in relation to the Delphini-1 project, granted me access, as the only student, to the Aarhus University Scientific board in relation to current and future satellite missions at the university.
I have now finished my master thesis project which is a 60 ECTS full year project. My thesis involved a danish mineral exploration company, who had been acquiring physical ground samples from Greenland over a period of 20 years. I was combining these data with remote sensing data from the ESA Sentinel satellites, as well as magnetic field measurements from aerial fly-overs and gravity maps. By applying machine learning techniques, I was attempting to be able to predict mineralization in regions with no current geological data. A part of the expertise gathered from this project, have aided me in landing a job as a geophysicist.
I am currently employed as a Geophysicist at Qeye Labs in Copenhagen, where I have been since August, 2019.
My job consist mostly of qualitative inversion of seismic data and seismic preconditioning. However the job span quite broadly and are therefore involved in rock physics modelling, CPT analysis, direct probability inversion and much more. All of this is done in our own software which is written in Python. Therefore a large part of my role is that of a data scientist, but with good knowledge physics and geological specialization.
Feel free to contact me if you have any questions
You can download my CV as a PDF here: