Data analyst at LUDC - Hiring in process/Finished, not possible to apply

The Lund University Diabetes Centre (LUDC; www.ludc.med.lu.se) opens a position for a Data Analyst. LUDC is one of the largest diabetes research centers in the world with approximately 300 investigators and staff members working towards improved diagnosis, prevention and treatment of diabetes. The Centre combines expertise in genetics, epidemiology, statistics, bioinformatics, molecular and cellular biology, physiology and clinical diabetes and endocrinology to achieve these goals. LUDC has large unique biobanks and databases with genome-wide data linked to national registries providing information on disease etiology, progression as well as outcome and treatment. The Centre has in-house platforms for most molecular genetic methods and metabolomics. Omics-information combined with extensive phenotyping allows a systems medicine approach to dissect the complexity of diabetes. A central theme of the Centre is to develop precision medicine to improve health and the quality of life of diabetic patients.

Job description:

The applicant will spend about 80% of their time reorganizing and cleaning data (renaming, recoding, checking data consistency), as well as performing statistical analyses on data from a large 15-year longitudinal study (and possibly other cohorts) working closely with biostatisticians and clinicians. About 20% of the time will be spent on documenting the cleaning process and contributing to manuscript preparation.

The successful applicant will:

• Be proficient in R or Python, have experience working with real data and using R Markdown (or some other tool used in reproducible research), as well as being organized and detail-oriented.
• Will work closely with experienced researchers on real data from large, longitudinal cohorts in a rigorous and reproducible manner, as well as gain valuable experience in working with real data and in manuscript writing.

Applicants from abroad will be eligible for Lund University visiting researcher housing.

Qualifications:

• BSc or MSc preferably in Computer Science, Statistics, Biostatistics, Mathematical Statistics or another quantitative discipline.
• Good working knowledge of R or Python and experience using R markdown, with additional programming experience preferred.
• Experience working with real data.
• Experience with Linux and using version control such as Git is a plus. Knowledge of applied statistics is a plus, but not required.

For further information please contact:

Marlena Maziarz marlena.maziarz@med.lu.se 

Carin Andrén Aronsson carin.andren_aronsson@med.lu.se