Astroinformatics for Students

 

Semester-and Bachelor Projects

BSc Computer Science | Data Science | ICT

Recent semester- and bachelor projects

Master Projects

MSc Computer Science | Data Science | ICT

Opportunities for master students

Are you interested in working towards a Master’s Thesis in Computer Science, combining computer science and machine learning with applications in science and space?
There are opportunities in the following research projects: RODEM, AstroSignals, SMILE/SXI, STIX, Euclid.

2020-2023 

Master students: Marius Giger, Anya Liebendörfer, Manuel Stutz (ab 2021)

PhD Positions

Computer Science and Solar Physics

2020

Open Position for RODEM. Contact andre.csillaghy (at) fhnw.ch
Open position for Euclid to be announced, soon. Contact martin.melchior (at) fhnw.ch

Current PhD Positions

Spectrum of a solar flare

Yana Shtyk, PhD candidate
Research project: RODEM
Partner academic institution: University of Geneva

Tbd.

Solar Orbiter

Andrea Battaglia, PhD candidate
Research project: STIX
Partner academic institution: ETH Zürich

A co-investigator in the STIX team, Andrea is responsible for the commissioning and operation of the STIX instrument onboard Solar Orbiter. Additionally, he analyzes STIX data with the goal of better understanding electron accelerations in solar flares.

Recent PhD Positions

Erica Lastufka, Doctoral degree 2020
Research project: MiSolFA
Partner academic institution: ETH Zürich

Erica worked on the gratings for the Imager on the Micro Solar Flare Apparatus, a micro-satellite designed to operate together with the X-ray telescope STIX to observe solar flares from a stereo perspective.

Matej Kuhar, Doctoral degree 2018
Research project: NuSTAR space telescope
Partner academic institution: ETH Zürich

Matej studied new observational techniques for solar flares, including micro flares, towards a better understanding of the coronal heating problem.

Brandon Panos, Doctoral degree 2021
Research project: IRIS Big Data
Partner academic institution: University of Geneva

Brandon used machine learning techniques such as t-SNE, GANs and LSTMs to perform large scale statistical studies on IRIS satellite data, to better understand the physics of solar flares.

Stefan Müller, Doctoral degree 2016
Research project: Dark Energy Survey
Partner academic institution: ETH Zürich

Stefan developed the semi-automatic parallelization software Pydron for astroinformatics including multi-core and the cloud.