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Cecilia Høst Ramlau-Hansen

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Postdoc in Genetics of Puberty Aarhus University in Denmark

Degree Level

Postdoc

Field of study

Biology

Funding

Funded by the Pioneer Centre for Statistical and Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed). Full-time postdoc salary is DKK 493,394.35 to DKK 585,322.48 per year depending on experience, including position-related supplement and pension (18.07%).

Deadline

Nov 10, 2026

Country flag

Country

Denmark

University

Aarhus University

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Keywords

Biology
Medical Science
Salud Pública
Molecular Epidemiology
Quantitative Genetics
Puberty
Statistics
Bioinformatic

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About this position

Postdoc in genetics of puberty at Aarhus University is a research-focused position in the Department of Public Health, Faculty of Health. The project sits within epidemiology, environment and biostatistics and is embedded in a strong research environment with around 200 colleagues, including many academic staff and PhD students.

The successful postdoc will work on a project in reproductive and molecular epidemiology that combines methodological development with applied human genetics. A key part of the research is developing more efficient approaches for GWAS of ordinal traits such as the Tanner Scale, leveraging information from genetically correlated traits like age of menarche and voice breaking, and deriving a polyproteomic score for pubertal development. The applied component uses Mendelian randomization to investigate how pubertal development relates to disease susceptibility.

The position is jointly supervised by researchers across Aarhus University, bringing together expertise from public health, clinical genetics, and quantitative genetics. The postdoc will work closely with colleagues at the Department of Public Health and the Center for Quantitative Genetics and Genomics, and is expected to engage with SMARTbiomed activities, including meetings and an annual symposium. The project also connects to a wider international collaboration involving Aarhus University, the University of Oxford, and the University of Copenhagen.

The role is based at Aarhus University in Aarhus C, with the expectation of spending roughly half of the time at each of two Aarhus University locations near the main campus. The advert emphasises independent, high-quality research and publication, together with collaboration across an internationally recognised environment.

Funding details

Funded by the Pioneer Centre for Statistical and Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed). Full-time postdoc salary is DKK 493,394.35 to DKK 585,322.48 per year depending on experience, including position-related supplement and pension (18.07%).

What's required

A relevant PhD degree is required. Applicants should have a background in data science, statistical genetics, quantitative genetics, bioinformatics, statistics, computer science, or a related field. Experience with computational analysis of large health datasets and electronic health records such as UK Biobank or All of Us is expected, along with experience performing GWAS analyses using tools such as PLINK, GCTA, or LDAK. Experience with register-based research is required. Candidates must have good interpersonal skills, be inclusive and team-oriented, contribute to a positive work environment, and be fluent in oral and written English. Shortlisting will be used.

How to apply

Submit the application through Aarhus University’s recruitment system via the job advertisement page. Include a motivated application, CV, diploma, applicant template, publications list, and teaching portfolio. Optional uploads include up to five key publications, a research plan, coauthor statements, and references or recommendations.

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Professors

Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Statistics

Quantitative Genetics

Molecular Epidemiology

Biology

Medical Science

Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Biostatistics

Statistics

Genome-wide Association

Quantitative Trait Loci (qtl) Mapping

Genetic