Are you an experienced analyst with an interest in epidemiology and statistical analyses of health data? Are you excited by working with state-of-the-art computational methods in an international medical research environment – and to handle data all the way – from data-cleaning, interpretation and analysis to publication?
COPECARE is an internationally renowned research unit in clinical rheumatology with a staff of four professors, 8 post.docs, 15 PhD students, data team, research nurses, lab technician and administrative staff. We aim to expand our current data team and therefore we are looking for a new colleague with a background in data science, (bio)statistics, bioinformatics or similar expertise within computational research – and with an interest in epidemiology and health care registries. You will join our current team of 3 data scientists with complementary skills across a range of research fields. Your tasks will be to take part in managing computational parts of interdisciplinary medical research projects combining clinical and registry data, genetic and serological biomarkers and medical imaging in rheumatology in an international clinical research environment. You will handle data all the way from data cleaning, interpretation and analysis to publication. The major projects for the data team are:
The NORA project is a Nordic collaborative effort between Danish, Swedish and Norwegian academic institutions aiming to explore serological and genetic biomarkers associated with treatment effects and prognosis in rheumatoid arthritis. A fully merged dataset including a wide range of results from biomarker analyses and clinical outcome data from historic observational and clinical trial cohorts will serve as the basis for a range of explorative and confirmative analyses. A core team of statistical and clinical experts with representation from the three countries is currently being established.
The EuroSpA project is a Research Collaboration Network established in 2016 in the field of axial spondyloarthritis and psoriatic arthritis with participants from 16 European countries aiming to address research questions regarding real-world treatment of arthritis patients across Europe by pooling relevant data variables from patient registries. The collaboration is currently expanding to include collection and assessment of MRI and X-rays. EuroSpA is led by an international Scientific Committee and supported by a Coordinating Centre located at COPECARE.
In collaboration with your data team colleagues and the principal investigators/clinical researchers, you will be responsible for handling of all types of data in the projects and contribute to the data flow from the raw data are extracted to the final analyses are published in international scientific journals. Specifically, you may
- Take part in preparation of new studies by developing data models based on study protocols
- Receive and screen clinical data from the participating EuroSpA registries and participate in the data-cleaning process
- Receive and manage imaging (DICOM)-files from registries and develop algorithms for automatic anonymization
- Pool clinical and imaging data and prepare analytical datasets
- Plan and conduct statistical analyses
- Contribute to scientific papers and study reports
- Communicate with European data managers, physicians, scientific programmers and IT-developers
Salary and terms of employment
The position is fulltime (37 hours/week) for 2 years with the possibility for extension. The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.
We are looking for a candidate with
- A Master’s or PhD degree in data science, (bio)statistics, bioinformatics, applied mathematics or similar
- Expertise in scientific programming in R
- Experience with collating complex data and creating an overview
- Experience in statistical analyses and data visualization
- Experience with epidemiological methodology
- Experience with reading code and collaborative software development using GIT
- A focus on delivering high quality data and analyses
- Familiarity with documentation of data processes
- The ability to work independently and as part of a team
- Excellent interdisciplinary communication skills
- Experience with analyses on genetic data and biomarkers
- An exciting position with enthusiastic and collaborative colleagues
- A possibility to be part of a research group at the highest international level
- A multi-disciplinary innovative group
- Flexible hours and good work-life balance