Bioinformatician, Genetic and Molecular Epidemiology - Hiring in process/Finished, not possible to apply

The Genetic and Molecular Epidemiology Unit runs several major national and international projects focused on understanding the role of genomic and lifestyle factors in complex metabolic diseases like diabetes, obesity and CVD. The Unit has led major projects funded by the National Institutes of Health, European Research Council and Innovative Medicines Initiative, several of which are ongoing. We are currently seeking to recruit one or more talented and enthusiast data analysts.

 The Unit currently hosts several doctoral students, post-docs and junior faculty. The Unit seeks to fill one or more new appointments in the fields of statistical genetics, bioinformatics, and/or biostatistics. The successful applicant(s) will be expected to work in a support role to the group leader (Prof. Franks) and other members of his team within a range of projects, including those conducted solely by the GAME Unit through large-scale international collaborations.

 The successful applicant will be expected to work the vast majority of her/his time at the Unit’s workspace at the CRC, Malmö. Occasional international travel for training and collaboration meetings will be necessary.

Work duties

The successful applicant will have a strong background in at least one of the following:

statistical genetics, including analysis of GWAS (or similar) datasets, including all standard procedures such as genotype imputation, meta-analysis, and in silico functional annotation

bioinformatics, with experience combining multiomics datasets including array and sequence data for gene expression and DNA methylation, and metabolomics, and in silico functional annotation

biostatistics, with experience in survival analysis, interaction modeling, and prediction analyses

Knowledge of epidemiological methods and of cardiometabolic disease is preferred, although not essential.

Qualifications

Essential characteristics:

 A PhD (or possibly master’s degree) in statistical genetics, bioinformatics, or biostatistics

At least 1-year post-doctoral experience working in the aforementioned fields

Proven ability to work to tight deadlines

Good (English language) writing skills

Excellent grasp of R and Stata. Familiarity with other programming languages such as Python, C++, or PEARL is preferred

Willingness to provide mentorship to group members

Enthusiasm to predominantly work to provide analytical support to on-going projects

Eagerness to work within a vibrant team setting and interact regularly with international collaborators

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset. We kindly decline all sales and marketing contacts.