H2020 NEMESIS postdoctoral/PhD positions in star formation using machine learning techniques
We invite applications for postdoctoral and PhD student positions in star formation using machine learning techniques. The successful candidate(s) will work with members of the recently established project NEMESIS, and in particular with Odysseas Dionatos (U. Vienna), Marc Audard (U. Geneva) and Gabor Marton (Konkoly Obs.), however, candidates will have the opportunity to spend extended working visits at the other participating institutes.
NEMESIS is a H2020 funded project (grant agreement 101004141; https://nemesis.univie.ac.at/) that has the ambition to reshape our understanding on the formation of stars by employing artificial intelligence methods to compile and interpret the largest, panchromatic data collection of young stellar objects.
The successful candidates should have a solid background (experience) in at least one of the following topics: star formation, classification of young stellar objects, application of machine learning techniques in large datasets. Candidates for the postdoc positions must hold PhD in astrophysics or in a closely related discipline, or have completed their MSc studies (or equivalent) for the PhD positions. Starting date can be as early as June 1st but no later than December 1st, 2021.
Applicants should send to email@example.com
• Cover letter
• CV and Publication list if applicable
• 5-page (maximum) statement of research, outlining any research experience so far
• For PhD student applicants: copy of Bachelor and master academic records (exams, grades).
• Candidates should also provide the names and contact details for at least two references.
Applications submitted until the 30th of May 2021 will receive full consideration, however later applications may be considered until all positions are filled. For further inquiries please write to firstname.lastname@example.org
Further details on the NEMESIS project can be found at https://nemesis.univie.ac.at/