HeaDS lists additional data science groups, courses and resources at the Faculty of Health and Medical Sciences.
Pharmaceutical sciences have traditionally been driven by experimental observations. However, the recent development within data science has enabled totally new ways to understand drug related research data. Pharma DS is leveraging big data challenges within multiple research areas ranging from drug effects at a receptor level and biological effects of the drug, to design of medicinal products and observational patient data.
The PharmaDS is made up by a team of data scientists and course managers that will strengthen the data science as an element across research and teaching. Specifically, PharmaDS will:
- Synergise strong drug-related research with strengthening of big data science.
- Establish infrastructure and support for swift integration of big datasets from Pharma DS, large scale research infrastructures and other public resources.
- Tailor big data into existing and new courses to fill an educational need of the life science industries.
- Increase the accessibility of data science expertise and resources to scientists.
- Profile our research data, e.g. via online research hubs developed in the Pharma DS team
- Complete the integration of databases with person-sensitive information and allow linkage in secure environments, e.g. Statistics Denmark and the Danish Health Data Authority
- Facilitate the access to larger data science infrastructures, e.g. Computerome and other European computer clusters
|Level||No. stud||Title||Data Science element||Course leader|
||50||Pharmaceutical Modelling||Machine learning and multivariate data analysis||Anders Ø. Madsen|
|MSc||25||Pharmacoepidemiology and Pharmacovigilance||Pharmaco-
|Morten Andersen &
|MSc||20-30||Advanced Manufacturing of Pharmaceuticals||Exploratory data sciences and data mining||Jukka Rantanen|
|PhD||20-30||Register-based research: Pharmacoepidemiology -
drug use and safety
|PhD||20||Fundamentals of register-based pharmaco-
epidemiology: evidence synthesis, data sources,
and study design
|Morten Andersen &
|PhD||20-30||Receptor structure and function||Data science
Data science team members
The data science team combines data science research groups and course managers to facilitates data science across research and teaching.
|Albert Jelke Kooistra||Assistant professor|
|Alexander Sebastian Hauser||Postdoc|
|David E. Gloriam||Professor|
|Karla Andrea Frydenvang||Associate professor|
|Maurizio Sessa||Assistant professor, tenure track|
|Tommy Nørskov Johansen||Associate professor, head of studies|
|Trine Meldgaard Lund||Associate professor|