Publisher
source

University of Copenhagen

PhD Fellowship in Trained Immunity in Zebrafish at the University of Copenhagen University of Copenhagen in Denmark

Degree Level

PhD

Field of study

Immunology

Funding

PhD fellowship funded by the project Decoding innate immune signatures driving trained and adaptive immunity in fish using a high-resolution in vivo and in vitro zebrafish model, financed by the Independent Research Foundation Denmark. Full-time employment for up to 3 years under the 5+3 PhD scheme; salary follows Danish state academic agreements. No stipend amount is stated.

Deadline

Sep 20, 2026

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Country

Denmark

University

University of Copenhagen

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Keywords

Immunology
Molecular Biology
Biology
Innate Immunity
Veterinary Science
Aquaculture
Medical Science
Pathogen Biology
Host-pathogen Interaction
Immunization
Zebrafish Biology

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About this position

PhD fellowship at the University of Copenhagen in trained immunity in zebrafish, hosted by the Institute/Department of Veterinary and Animal Sciences and the Experimental Fish Models (Exfimo) research group.

The project studies how the innate immune system of fish contributes to protection against infectious diseases, with a focus on zebrafish (Danio rerio), neutrophils, macrophages, host–pathogen interactions, innate immunity, and adaptive immunity. Experimental work includes microinjection, infectious disease challenges, live imaging, molecular analyses, gene expression analysis, isolation of innate immune cells, in vitro stimulation, and functional assays. The project uses the parasite Ichthyophthirius multifiliis and the bacterium Vibrio anguillarum.

The fellowship is part of the project Decoding innate immune signatures driving trained and adaptive immunity in fish using a high-resolution in vivo and in vitro zebrafish model, funded by the Independent Research Foundation Denmark. The position is full-time for 3 years and starts 1 January 2027 or after agreement.

Applicants should have a relevant master’s degree and a background in immunology, infection biology, or molecular biology. Experience with zebrafish, advanced microscopy, cell-based assays, bioinformatics, or quantitative data analysis is an advantage. The group offers access to a well-established zebrafish facility, transgenic reporter lines, an international research environment, and opportunities for teaching, collaboration, and development of independent ideas.

Deadline: 20 September 2026, 23:59 CET. Apply through the university portal with a motivation letter, CV, diploma/transcript, and publication list if available.

Funding details

PhD fellowship funded by the project Decoding innate immune signatures driving trained and adaptive immunity in fish using a high-resolution in vivo and in vitro zebrafish model, financed by the Independent Research Foundation Denmark. Full-time employment for up to 3 years under the 5+3 PhD scheme; salary follows Danish state academic agreements. No stipend amount is stated.

What's required

Applicants should have a relevant academic degree at master’s level equivalent to a Danish master’s degree in a subject area relevant to the project. A background in immunology, infection biology or molecular biology is preferred. Experience with zebrafish work, advanced microscopy, host–pathogen interactions, innate immunity, vaccination, gene expression analysis, cell-based assays, microinjection, in vivo imaging, molecular techniques, immune-cell isolation, quantitative data analysis or bioinformatics is advantageous but not required. Applicants should have relevant publications, relevant work experience, other relevant professional activities, a curious mindset, strong interest in immunology, and good language skills.

How to apply

Apply electronically via the university’s Apply now portal. Submit a motivated letter, CV, certified MSc diploma and transcript (with English translation if needed), and a publication list if possible. Ensure your master’s degree is equivalent to a Danish master’s degree and submit before the deadline.

More information can be found here

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