Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and more than 8 000 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.
The Faculty of Medicine is a part of Lund University, and is responsible for education and research within medicine and healthcare. Our academic programs are closely linked with the healthcare system and are firmly anchored in the faculty’s strong research tradition. Our research spans a broad field within experimental preclinical research, near-patient clinical research and health sciences research. The Faculty of Medicine, with its 1,800 employees and 2,700 students in Lund and Malmö, is a knowledge-intensive meeting place for students, teachers and researchers from all over the world.
The Department of Clinical Sciences, Malmö is one of the six departments at the Faculty of Medicine, Lund University. We have a strong focus on clinical and epidemiological research and also conduct an extensive preclinical laboratory research.
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.
Type of employment | Temporary position longer than 6 months |
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Contract type | Full time |
Number of positions | 2 |
Working hours | 100 |
City | Malmö |
County | Skåne län |
Country | Sweden |
Reference number | PA2018/3760 |
Contact |
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Union representative |
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Published | 16.Nov.2018 |
Last application date | 31.Jan.2019 11:59 PM CET |