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Doctoral student in Galactic archaeology with 4MOST Lund University in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Dec 4, 2026
Country
Sweden
University
Lund University
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About this position
This PhD project sits within Lund University’s long-standing involvement in the 4MOST spectroscopic survey and focuses on Galactic archaeology. The doctoral student will work with spectroscopic observations of stars in the Milky Way to investigate the origins of the Galaxy and how its stellar populations formed and evolved.
The position is based in the research environment at Lund University, where several researchers play leading roles in 4MOST surveys and in the working groups that analyse the raw data. The project gives access to data that will be released continuously over the next five years, making it a data-rich and evolving research topic within observational astronomy.
The successful candidate will analyse stellar spectra and may also have opportunities to develop new observational projects. The work is framed within doctoral education in astronomy and astrophysics, with a strong emphasis on independent research, publication, participation in project meetings within Lund and the wider 4MOST consortium, and presentation of results at conferences.
As a doctoral student, you will be trained in a scientific approach while contributing to an active international survey collaboration. The employment is full-time and fixed-term, and teaching or other departmental work may extend the appointment accordingly.
Funding details
Available
What's required
Applicants must have a second-cycle qualification, or at least 240 credits with at least 60 second-cycle credits, or equivalent knowledge. For the third-cycle programme in Astronomy and Astrophysics, candidates must have substantial study in physics, mathematics and/or corresponding engineering subjects, including at least 60 credits in basic physics and at least 30 credits in astronomy or other relevant physics/engineering subjects, with the 90 credits including at least 45 second-cycle credits; equivalent prior learning may be assessed individually. The applicant should have good ability to work independently and to formulate and tackle research problems, strong written and oral communication skills, good ability to cooperate, and very good English (spoken and written). Merits include strong numerical and analytical problem-solving skills, programming experience especially in Python, experience analysing stellar spectra, and experience with statistical analysis of large datasets.
How to apply
Apply in English via the university’s Varbi portal. Attach a CV, a personal letter explaining your interest and fit for the project, copies of study certificates and/or diplomas proving eligibility, and any other supporting documents such as grades, references, or recommendation letters.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.